BR112016025109B1 - BLOCK-BASED STATIC REGION DETECTION FOR VIDEO PROCESSING - Google Patents

Abstract

BLOCK-BASED STATIC REGION DETECTION FOR VIDEO PROCESSING. These are methods, apparatus, systems, and articles of manufacture for performing block-based static region detection for video processing. Exemplary video processing methods disclosed include segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks. Such exemplary methods may also include processing the first plurality of pixel blocks and a second plurality of pixel blocks corresponding to a previous second frame of the video sequence to create, based on a first criterion, a map that identifies one or more blocks. pixel blocks in the first plurality of pixel blocks. Such exemplary methods may further include identifying, based on the map, a static region in the first frame of the video sequence.

Description

FIELD OF INVENTION

[001] This disclosure relates generally to video processing and more particularly to block-based static region detection for video processing.

HISTORIC

[002] In video processing, static region detection involves identifying one or more regions of a video frame that are static or unchanging with respect to a previous video frame in a video sequence. By identifying the static region(s) in a video frame, such static region(s) can then be preserved and/or used( s) during subsequent video processing operations, such as frame rate upconversion and/or video compression.

BRIEF DESCRIPTION OF THE DRAWINGS

[003] Figure 1 is a block diagram of an example video processing system that includes a static region detector that employs block-based static region detection, as disclosed herein.

[004] Figures 2A and B and 3A and B illustrate example image artifacts that may be created by prior video processing systems that do not employ block-based static region detection as disclosed herein.

[005] Figure 4 is a block diagram illustrating an example implementation of the static region detector of Figure 1.

[006] Figure 5 illustrates an example operation of the example static region detector of Figure 4.

[007] Figure 6 is a block diagram of an example static block criteria evaluator that can be used to implement the example static region detector of Figure 4.

[008] Figures 7A and B illustrate an example operation of the example static block criteria evaluator of Figure 6.

[009] Figure 8 is a block diagram of an example static block criteria adjuster that can be used to implement the example static region detector of Figure 4.

[010] Figure 9 is a block diagram of an example static map combiner that can be used to implement the example static region detector of Figure 4.

[011] Figure 10 illustrates example operation results that can be achieved by the example video processing system of Figure 1.

[012] Figure 11 is a representative flowchart of example machine-readable instructions that can be executed to implement the example static region detector of Figures 1 and/or 4.

[013] Figure 12 is a representative flowchart of example machine-readable instructions that can be executed to implement the example static block criteria evaluator of Figure 6 and/or the static block criteria evaluation and map criteria static region detector in the example static region detector of Figures 1 and/or 4.

[014] Figure 13 is a representative flowchart of example machine-readable instructions that can be executed to deploy the example static map combiner of Figure 9 and/or the static map combiner in the example static region detector of Figures 1 and/or 4.

[015] Figure 14 is a representative flowchart of example machine-readable instructions that can be executed to implement the example static block criteria adjuster of Figure 8 and/or the static block criteria adjustment in the static region detector example of Figures 1 and/or 4.

[016] Figure 15 is a block diagram of an example processor platform that can execute the example machine-readable instructions of Figures 11 to 13 and/or 14 to implement the example video processing system of Figure 1 , the example static region detector of Figures 1 and/or 4, the example static block criteria evaluator of Figure 6, the example static block criteria adjuster of Figure 8, and/or the example static block map combiner of example in Figure 9.

[017] The material disclosed in this document is illustrated by way of example and not by way of limitation in the attached figures. For simplicity and clarity of illustration, the elements illustrated in the figures are not necessarily drawn to scale. For example, the dimensions of some elements may be exaggerated relative to other elements for clarity. Furthermore, whenever possible, the same reference numbers will be used throughout the drawing(s) and attached written description for reference to parts, elements, etc. the same or similar. DETAILED DESCRIPTION

[018] Disclosed herein are methods, apparatus, systems and articles of manufacture (e.g., physical storage media) for implementing block-based static region detection for video processing. Some example video processing methods disclosed herein include segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks. Some such exemplary methods also include processing the first plurality of pixel blocks and a second plurality of pixel blocks corresponding to a previous second frame of the video sequence to create, based on one or more criteria, a map that identifies a or more static pixel blocks in the first plurality of pixel blocks. Some such example methods further include identifying, based on the map, one or more static regions in the first frame of the video sequence.

[019] In some disclosed example methods, processing the first plurality of pixel blocks and the second plurality of pixel blocks includes evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on a first criterion to determine a first static block identification result. Some such example methods also include evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on a second criterion to determine a second static block identification result. Some such example methods further include combining the first and second static block identification results to create the map that identifies the one or more static pixel blocks in the first plurality of pixel blocks.

[020] In some disclosed example methods, the one or more criteria include a sum of absolute differences criterion. In such exemplary methods, processing the first plurality of pixel blocks and the second plurality of pixel blocks includes computing a sum of absolute differences between pixels in a first pixel block of the first plurality of pixel blocks and the corresponding pixels in a corresponding second pixel block of the second plurality of pixel blocks. Some such example methods also include determining whether the first pixel block is a static block based on comparing the sum of absolute differences to a threshold.

[021] In some disclosed example methods, the one or more criteria include an edge count criterion. In some such exemplary methods, processing the first plurality of pixel blocks and the second plurality of pixel blocks includes determining an edge map that identifies edges in the first frame of the video sequence. Some such example methods also include counting a number of pixels in a first pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map. Some such example methods further include determining whether the first pixel block is a static block based on comparing the number to a threshold.

[022] In some disclosed example methods, the one or more criteria include an edge matching criterion. In some such exemplary methods, processing the first plurality of pixel blocks and the second plurality of pixel blocks includes determining a first edge map that identifies edges in the first frame of the video sequence. Some such example methods also include identifying the first edge pixels in a first pixel block of the first plurality of pixel blocks, wherein the first edge pixels are associated with the edges identified in the first edge map. Some such example methods further include determining a number of first edge pixels that have no edge correspondence with respective second edge pixels in a corresponding second pixel block of the second plurality of pixel blocks. For example, two edge pixels can be edge-matched when the two edge pixels have the same frame location and are associated with the same edge orientation. Some such example methods further include determining whether the first pixel block is a static block based on comparing the number to a threshold.

[023] In some disclosed example methods, the first frame has multiple video components, the first plurality of pixel blocks is associated with a video component foreground, and the map is a first map. Some such example methods include segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a video component background different from the video component foreground. Some of such exemplary methods also include processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the video component background of the previous second frame of the video sequence to create, based on the one or more criteria , a second map that identifies one or more static pixel blocks in the third plurality of pixel blocks. Some such example methods include identifying, based on the first and second maps, the one or more static regions in the first frame of the video sequence. In some such examples, identifying the one or more static regions in the first frame includes combining the first map and the second map to determine an overall map that identifies the one or more static pixel blocks in the first frame of the video sequence.

[024] In some disclosed example methods, the map is a first map. Some such example methods include segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks such that those of the third plurality of pixel blocks partially overlap those of the first plurality of blocks. Some such exemplary methods also include processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the previous second frame of the video sequence to create, based on the one or more criteria, a second map that identifies a or more static pixel blocks in the third plurality of pixel blocks. In some such examples, those of the fourth plurality of pixel blocks partially overlap those of the second plurality of blocks. Some such example methods include identifying, based on the first and second maps, the one or more static regions in the first frame of the video sequence. In some such examples, identifying the one or more static regions in the first frame includes combining the first map and the second map to determine an overall map that identifies one or more static pixel sub-blocks in the first frame of the video sequence. For example, a first sub-block in the first frame is included in a first block of the first plurality of pixel blocks and a first block of the third plurality of blocks, and the overall map has better resolution than the first and second blocks. Some such example methods also include identifying one or more static regions in the first frame of the video sequence based on the overall map.

[025] In some disclosed example methods, the map is a first map. Such an exemplary method may also include adjusting a first criterion among the one or more criteria based on at least one of (1) a determined correlation between the first and second frames of the video sequence or (2) evaluating a second map prior that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second preceding frame of the video sequence.

[026] These and other example methods, apparatus, systems, and articles of manufacture (e.g., physical storage media) for implementing block-based static region detection for video processing are disclosed in more detail below.

[027] As mentioned above, static region detection involves identifying one or more regions of a video frame that are static or unchanging with respect to a previous video frame in a video sequence. An identified static region can then be preserved and/or leveraged, if appropriate, during subsequent video processing operations, such as frame rate upconversion and/or video compression. However, false detection of a static region in an image frame can produce undesirable artifacts in moving regions of a video sequence. Similarly, missed detection of a static region or, in other words, misprediction of motion in what is actually a static region can produce undesirable artifacts in non-motion regions of a video sequence. As discussed in more detail below, the examples disclosed herein employ block-based static region detection and, in at least some examples, multiple detection criteria, which can reduce the likelihood of false and/or missed region(s) detection. ) static(s) in a video sequence.

[028] Turning to the figures, a block diagram of at least a portion of an example video processing system 100 that employs block-based static region detection, as disclosed herein, is illustrated in Figure 1 The video processing system 100 of the illustrated example processes an example input video sequence 105 to produce an example output video sequence 110. The video sequences 105 and 110 each include a series of video frames. sequential videos (also referred to as images, image frames, etc.). A video frame in video sequences 105 or 110 may include one or more video components, wherein each video component corresponds to a respective component plane of the video frame. For example, to support color video, a video frame in video sequences 105 or 110 may include a luminance component (also referred to as the Y component) and two chrominance components (also referred to as the U and V components), and such a video frame can be decomposed into one luminance component plane and two chrominance component planes. Other video frame representations that have different components, and/or more or fewer components, may be supported by the video processing system 100 and the block-based static region detection techniques disclosed herein.

[029] In the illustrated example of Figure 1, the video processing system 100 includes an exemplary static region detector 115 that implements block-based static region detection, as disclosed herein, to detect one or more static regions in a video frame of the input video sequence 105. In general, a static region of a video frame of the input video sequence 105 is a region of the video frame that is static, or unchanging, with respect to a video frame of the input video sequence 105. preceding video in the input video sequence 105. Conversely, a region of the video frame that changes with respect to the same region of the preceding video frame in the input video sequence 105 is considered to be a region associated with motion. An example implementation of the static region detector 115 is illustrated in Figure 4, which is described in more detail below.

[030] The static region(s) identified by the illustrated static region detector 115 may be preserved during subsequent video processing operations (e.g., to improve quality of the video, avoiding the introduction of artifacts in the static region(s)). The identified static region(s) can be additionally or alternatively leveraged during subsequent video processing operations (e.g., to improve video compression performance by taking advantage of redundancies in the video sequence). For example, in the illustrated example of Figure 1, the static region detector 115 provides information that identifies the detected static region(s) of a video frame in the input video sequence 105 at a example frame rate upconverter 120. The frame rate of a video sequence refers to the number of frames of the video sequence that correspond to a given time interval. For example, frame rate may be expressed in units of frames per second (fps), Hertz (Hz), etc., or any other suitable units. Typical video frame rates may include, for example, 15 fps (or 15 Hz), 30 fps (or 30 Hz), 60 fps (or 60 Hz), 120 fps (or 120 Hz), etc. In general, frame rate upconversion involves processing the input video sequence 105, which has a first frame rate (e.g., 60 fps or 60 Hz), to produce an output video sequence 110 that presents the same set of video images having a second higher frame rate (e.g., 120 fps or 120 Hz). The frame rate upconverter 120 of the illustrated example deploys any number and/or type(s) of framerate upconversion techniques to increase the framerate between the input video stream 105 and the input video stream. output 110. For example, frame rate upconverter 120 may deploy interpolation to insert a new video frame between two existing frames of input video sequence 105, prediction to predict a new video frame from one or more existing frames of the input video sequence 105, other techniques, or any combination thereof.

[031] In the illustrated example of Figure 1, the frame rate upconverter 120 receives the static region(s) identified by the static region detector 115 in video frames of the video sequence of The example frame rate upconverter 120 may then use information to preserve static regions in the video frames of the input video sequence 105 during upconversion to form the output video sequence 110. Examples of image artifacts that may be introduced by frame rate upconversion into the output video sequence 110 if static regions are not adequately preserved are illustrated in Figures 2A and B and 3A and B. For example, Figure 2A represents an example video frame from example input video sequence 105. Figure 2B depicts a corresponding upconverted frame from example output video sequence 110, which exhibits noticeable artifacts (e.g., such as blurring) that may be caused by frame rate upconversion that exhibits missed detection of static regions (or, in other words, false motion detection). Figure 3A represents an example video frame from another example input video sequence 105. Figure 3B represents a corresponding upconverted frame from example output video sequence 110, which exhibits noticeable artifacts (e.g., such such as blocking) that may be caused by frame rate upconversion that exhibits false detection of static regions. Block-based static region detection, as disclosed herein and employed by example static region detector 115 of Figure 1, reduces the likelihood of false and/or missed detection of static region(s) in the sequence of input video 105, which reduces the likelihood that the output video sequence 110 will exhibit the unwanted artifacts illustrated in the examples of Figures 2B and/or 3B.

[032] In the illustrated example, the video processing system 100 further includes an example motion estimator 125. The illustrated example motion estimator 125 determines, using any suitable technique or combination(s) of techniques , motion data to characterize motion between successive video frames of input video sequence 105. For example, motion data determined by motion estimator 125 may include, but is not limited to, one or more motion vectors, indices reference, interdirections, etc. In the illustrated example of Figure 1, motion data determined by motion estimator 125 may be used by frame rate upconverter 120 to interpolate, predict, and/or otherwise create new frames for inclusion in the output sequence 110 that it considers. the motion displayed in the video frame of the input video sequence 105. In some examples, the motion estimator 125 may use static region information provided by the static region detector 115 to improve accuracy, quality, etc. of the determined movement data. Additionally or alternatively, in some examples, the static region detector 115 may use the motion data determined by the motion estimator 125 to verify the accuracy of the static region(s) detected using block-based static region detection as disclosed herein. The operation of the static region detector 115 to verify static region detection using motion data is disclosed in more detail below.

[033] Although block-based static region detection is described in the context of the example video system 100 of Figure 1, block-based static region detection, as disclosed herein, is not limited to the same. For example, block-based static region detection as disclosed herein is not limited to use with frame rate upconversion, but may be used with additional or alternative video processing techniques, such as video compression. video, etc.

[034] A block diagram of an example implementation of the static region detector 115 of Figure 1 is illustrated in Figure 4. The example static region detector 115 of Figure 4 employs block-based static region detection, which can be more robust and yield a lower possibility (or probability) of false and/or missed static region detections than previous static region detection techniques. Furthermore, block-based static region detection, as disclosed herein, lends itself to a higher level of vectorization than previous techniques involving comparison of individual image pixels, which can result in cost-effective deployment. of static region detector 115 in hardware.

[035] In the illustrated example, the static region detector 115 of Figure 4 performs static region detection independently on the different video component planes of a video frame in the input video sequence 105. For example, the region detector static region 115 of Figure 4 performs static region detection independently of the luminance plane (Y) and the two chrominance planes (U/V) of the input video frame. As disclosed in more detail below, the example static region detector 115 of Figure 4 segments the video frames of the input video sequence 105 into pixel blocks and utilizes the three video components (e.g., one luminance and two chroma) of two successive video frames (e.g., a current and a previous frame) of the input video sequence 105 to create individual binary static maps for each of the video component planes undergoing processing. Each bit in a binary static map for a given video component plane of a video frame (e.g., the current video frame being processed) corresponds to a respective pixel block in the given video component plane of the video frame segmented and indicates whether the corresponding pixel block is a static block or not. In some examples, the same static block detection criteria are used for static block detection in each of the video component planes, while in other examples, different static block detection criteria may be used for different video component planes. video. Example static block detection criteria that may be employed by static region detector 115 are disclosed in more detail below.

[036] In the illustrated example of Figure 4, the static region detector 115 combines the binary static maps for the different video component planes into an overall binary static map that identifies the static pixel blocks in a video frame (e.g. , the current video frame being processed). In some examples, the static region detector 115 further processes the overall binary static map to improve detection reliability. The identified static pixel blocks may then be grouped into static regions and/or provided by static region detector 115 to other video processing modules, such as example frame rate upconverter 120. In some examples, Additional processing improvements are implemented by example static region detector 115 of Figure 4.

[037] The example static region detector 115 of Figure 4 includes an example video segmenter 405 for segmenting video frames from the input video sequence 105 into blocks of pixels, also referred to as pixel blocks. For example, video segmenter 405 may segment an input video frame into pixel blocks, each of which contains 16 x 16 pixels, which is suitable for supporting motion estimation algorithms for video sequences that are 1080 pixels in size. vertical resolution (1,080p). In other examples, video segmenter 405 may segment an input video frame into pixel blocks that have other sizes (e.g., 4 x 4 pixels, 8 x 8 pixels, etc.). Furthermore, in some examples, the size of pixel blocks determined by video segmenter 405 is programmable or otherwise configurable (e.g., via user input). In the example illustrated in Figure 4, video segmenter 405 segments each video component plane (e.g., the luminance plane and the two chrominance planes) to form three video component planes segmented from pixel blocks for a given input video frame (for example, represented by the “3” that identifies the output line of the video segmenter 405 in the example illustrated in Figure 4).

[038] The example static region detector 115 of Figure 4 also includes an example static block criteria evaluator 410 for processing the segmented video component planes provided by the video segmenter 405 to identify zero or more static pixel blocks in the respective video component planes of an input video frame. In the illustrated example, to identify zero or more static blocks in a current video frame (e.g., the first) of the input video sequence 105, the static block criteria evaluator 410 evaluates the pixel blocks in the current video frame. (e.g., the first) and corresponding pixel blocks in a preceding video frame (e.g., the second) of the input video sequence 105 against one or more static block detection criteria. If the static block detection criteria are satisfied by a given current/previous pixel block pair, the static block criteria evaluator 410 indicates that the corresponding pixel block in the current video frame is a static block. Examples of static block detection criteria that can be evaluated by the static block criteria evaluator 410 are disclosed in more detail below. In the example illustrated in Figure 4, the static block criteria evaluator 410 performs the static block evaluation individually for each video component plane (e.g., the luminance plane and the two chrominance planes) segmented by the video segmenter 405 Thus, for a given pixel block of a video frame, the static block criteria evaluator 410 produces separate static block detection results for each of the video component planes of a given input video frame (e.g. example, represented by the “3” that identifies the output line of the static block criteria evaluator 410 in the example illustrated in Figure 4). An example implementation of the static block criteria evaluator 410 is illustrated in Figure 6, which is described in more detail below.

[039] The example static region detector 115 of Figure 4 further includes an example static map creator 415 for creating a static map that identifies zero or more static pixel blocks determined by the example static block criteria evaluator 410. For example, the still map creator 415 may create a separate static map for each video component plane (e.g., the luminance plane and the two chrominance planes) segmented by the video segmenter 405 (e.g., represented by the “3” that identifies the output line of the static map creator 415 in the example illustrated in Figure 4). Each entry in a static map for a given video component plane of a video frame (e.g., the current video frame being processed) corresponds to a respective pixel block in the given video component plane of the segmented video frame and indicates whether the corresponding pixel block is a static block or not. For example, static maps created by static map creator 415 may be binary static maps in which each map entry is a bit that has a logical value of “1” or “0”. In such examples, for a given pixel block in a given video component plane of a corresponding input video frame, the static map creator 415 may set the corresponding bit in the binary static map for the given video component plane. into one of the logical values (e.g., “1” or “0”) to indicate that the given pixel block is a static block, and may set the corresponding bit in the binary static map for the given video component plane in the other logical value (e.g., “0” or “1”) to indicate that the given pixel block is not a static block. In the illustrated example of Figure 4, the static map creator 415 defines the roads of its static maps according to the evaluation results provided by the static block criteria evaluator 410.

[040] In the example illustrated in Figure 4, the static region detector 115 includes an example static map store 420 to store the static maps created by the example static map creator 415 for the different video component planes of a frame. of input video being processed. For example, if example video segmenter 405 segments an input video frame over three component video planes (e.g., one luminance plane and two chrominance planes), then static map storage 420 stores three static maps for the input video frame, a static map for each of the different video component planes. Example static map storage 420 may be implemented by any number and/or type(s) of memories, storage devices, etc., such as, but not limited to, memory 1514 and/or storage device 1528 of the example 1500 processor platform, which is described in more detail below.

[041] The example static region detector 115 of Figure 4 includes an example static map combiner 425 for combining the different static maps for a given input video frame (e.g., current) into an overall static map that identifies the zero or more static pixel blocks in the given input (e.g. current) video frame. For example, the static map combiner 425 of Figure 4 retrieves, from the example static map store 420, the static maps created by the example static map creator 415 for the three different video component planes (e.g., one for luminance and two for chrominance) of the given input (e.g., current) video frame (e.g., represented by the “3” identifying the input line in the static map combiner 425 in the illustrated example of Figure 4). The static map combiner 425 then combines the static maps for the different video component planes into an overall static map that identifies the zero or more static pixel blocks in the given input (e.g., current) video. Such combination is referred to herein as “intercomponent combination” due to the fact that static map combination is performed across two or more different video component planes. Example techniques that can be used by static map combiner 425 to combine static maps for different video component planes into an overall static map are disclosed in more detail below.

[042] In some examples, the static map combiner 425 of Figure 4 additionally or alternatively implements “intra-component combining”, which refers to combining multiple static maps that are associated with the same video component plane. Intracomponent combination may be used, for example, when example video segmenter 405 is configured to segment an input video frame from the input video sequence multiple times, with the pixel blocks in each segmentation iteration being shifted by relative to pixel blocks associated with other segmentation interaction(s). In such examples, pixel blocks determined by video segmenter 405 for the input video frame in one segmentation iteration will partially overlap with pixel blocks determined by video segmenter 405 in other segmentation iteration(s). segmentation. Block regions overlapped through different segmentation iterations define smaller sub-blocks. Thus, the resulting overall static map determined by the static map combiner 425 that performs intra-component combination of the static maps corresponding to the different segmentation iterations will have higher resolution corresponding to the smaller sub-block size. Due to the fact that the pixel sub-blocks represented in the overall static map determined by the static map combiner 425 in such an example are each associated with multiple static block decisions corresponding to the multiple pixel blocks that overlap a given sub-block, the accuracy of a static block decision for a given sub-block can be improved by combining the decisions for multiple pixel blocks that overlap the given sub-block.

[043] An example of overlapping video frame segmentation, which can be performed by example video segmenter 405, and corresponding intra-component combination, which can be performed by example static map combiner 425, is illustrated in Figure 5. Example of Figure 5 corresponds to an example scenario in which video segmenter 405 segments an input video frame over multiple iterations such that pixel blocks in successive iterations are offset by 50% (or half) of the block size of pixels in horizontal or vertical directions. For example, in a first example segmentation 505 illustrated in Figure 5, the video segmenter 405 begins segmenting in the upper left corner of the input video frame, which produces pixel blocks 510, etc., that have a size of 16 x 16 pixels, or some other size. In a second example segmentation 520 illustrated in Figure 5, the video segmenter 405 shifts the segmentation by 50% of the pixel block size (e.g., 8 pixels in this example) in the horizontal direction relative to the first example segmentation 505 to produce 525 pixel blocks, etc. In a third example slicer 530 illustrated in Figure 5, the video slicer 405 shifts the slicer by 50% of the pixel block size (e.g., 8 pixels in the example) in the vertical direction relative to the first example slicer 505 to produce 535 pixel blocks, etc. In a fourth example slicer 545 illustrated in Figure 5, the video slicer 405 shifts the slicer by 50% of the pixel block size (e.g., 8 pixels in the example) in the horizontal direction relative to the third example slicer 505 to produce 550 pixel blocks, etc.

[044] In the example of Figure 5, the example static block criteria evaluator 410 and the static map creator 415 perform static block criteria evaluation and static map creation for each of the different segmentation iterations 505, 520, 530, 545. For example, the static map creator 415 of the illustrated example outputs three static maps corresponding to the three different video component planes resulting from the first example segmentation 505, three static maps corresponding to the three different video component planes resulting of the second example segmentation 520, three static maps corresponding to the three different video component planes resulting from the third example segmentation 530, three static maps corresponding to the three different video component planes resulting from the fourth example segmentation 545, etc. As shown in the example of Figure 5, the pixel block 510 of the first example segmentation 505, the pixel block 525 of the second example segmentation 520, the pixel block 535 of the third example segmentation 530, and the pixel block 550 of the fourth example segmentation 545 all overlap an example subblock 560 (e.g., which is 8 x 8 pixels in the illustrated example). In the example illustrated in Figure 5, the static map combiner 425 may perform intra-component combination to combine, for a given video component plane, the different static maps corresponding to the different example segmentations 505, 520, 530 and 545 to determine a single combined static map for the given component video plane that has an entry for subblock 560. For example, the entry for subblock 560 in the combined static map for a given component video plane could be a combination of entries for pixel block 510, 525, 535, and 550 in the different static maps created for the different segmentation iterations 505, 520, 530, and 545. An example deployment of the static map combiner 425 of Figure 4 is illustrated in Figure 9 , which is described in more detail below.

[045] Returning to Figure 4, example static map combiner 425 combines static maps for different video component planes of a given input video frame (e.g., current) and/or for different segmentations of the given input video frame (e.g., current), to produce a single overall static map that identifies the static block(s), if any, in the given input video frame (e.g., current ) (e.g., represented by the “1” that identifies the output line of the static map combiner 425 in the example illustrated in Figure 4). In some examples, the static region detector 115 of Figure 4 includes an example media filter 430 to filter the overall static map for the given input (e.g., current) video frame to remove spurious entries that identify block(s). ) static or non-static isolated(s). Example median filter 430 may deploy any type of median filter and/or other filtering/post-processing to remove spurious static/non-static block identifications from the overall static map output by static map combiner 425. In some examples, additionally or As an alternative to processing the overall still map output by the still map combiner 425, the median filter 430 can be configured to filter/process the still maps determined by the still map creator 415 for the individual video component planes of the given image frame. input video (e.g. current).

[046] In the example illustrated in Figure 4, the static region detector 115 includes an example static region identifier 435 to output information that identifies the static region(s), if any, indicated by the static map general for a given input video frame (e.g. current). For example, the static region identifier 435 may output location information that identifies the static blocks indicated in the overall static map for the given input (e.g., current) video frame. In some examples, region identifier 435 combines static blocks of pixels indicated in the overall static map for the given input (e.g., current) video frame to form larger static regions and then outputs location/size/shape information. which specify the static regions in the given input (e.g. current) video frame.

[047] In some examples, the static region detector 115 of Figure 4 includes an example static region checker 440 to check the static region(s), if any, to be emitted by the example static region identifier 435. In the illustrated example of Figure 4, the static region checker 440 obtains verification information (e.g., from the example motion estimator 125) and compares this information with the static blocks/regions to be be emitted by the static region checker 440. Depending on the results of the check, the static region checker 440 may cause the static region information that is emitted by the static region identifier 435 to remain unchanged or it may cause all of the information to be changed (e.g., thus causing the static region(s) to be identified as non-static and/or vice versa). For example, the static region checker 440 may receive verification information in the form of motion data (e.g., motion vectors) from the example motion estimator 125. In such examples, the static region checker 440 compares the motion data for a given pixel block with the filtered static map input for the given pixel block. If the motion data indicates that the pixel block is associated with little to no motion (for example, if the motion data has small magnitude(s)), and the static map input identifies the pixel block as a static block, the identification of the pixel block as a static block remains unchanged. Similarly, if the motion data indicates that the pixel block is associated with no motion (for example, if the motion data has large magnitude(s)), and the static map input identifies the pixel block as a non-static block, the identification of the pixel block as a non-static block remains unchanged. However, if the motion data and the static map input differ (e.g., one indicates motion and the other indicates static, or vice versa), then the magnitude and/or reliability of the motion data entered into the verifier static region map 440 can be used to determine whether to change the static map input for the given pixel block. For example, if the motion data strongly indicates that a pixel block is associated with a region that has little or no motion, but the static map entry for that pixel block identifies the pixel block as a non-static block, then , the static region checker 440 may review the static map input to identify the pixel block as a static block. Conversely, if the motion data strongly indicates that a pixel block is associated with a region that has motion, but the static map entry for that pixel block identifies the pixel block as a static block, then the checker static region block 440 may review the static map input to identify the pixel block as a non-static block.

[048] In some examples, the static region detector 115 of Figure 4 includes an example static block criteria adjuster 445 to adjust the static block detection criteria by the example static block criteria evaluator 410. For example, The static block criteria adjuster 445 of some examples examines the correlation between the input (e.g., current) video frame being processed and the preceding frame to determine whether regions of the input video frame correspond to regions of movement or no movement. If appropriate, the static block criteria adjuster 445 may then adjust one or more of the static block detection criteria in the same way. As another example, the static block criteria adjuster 445 of some examples examines previous static maps determined by the static region detector 115 and applies hysteresis or other feedback to determine whether to adjust one or more of the static block detection criteria, and, If yes, by how much. An example implementation of the static block criteria adjuster 445 of Figure 4 is illustrated in Figure 8, which is described in more detail below.

[049] An example implementation of the static block criteria evaluator 410 of Figure 4 is illustrated in Figure 6. As mentioned above, the static block criteria evaluator 410 evaluates the pixel blocks in a current video frame (e.g. , the first) and corresponding pixel blocks in a preceding video frame (e.g., the second) of the input video sequence 105 against one or more static block detection criteria to identify zero or more static pixel blocks in the current video frame (e.g. the first). In some examples, the static block criteria evaluator 410 performs independent static block criteria evaluations for different video component planes of the current video frame (e.g., the first).

[050] Turning to Figure 6, the illustrated example static block criteria evaluator 410 includes an example block pixel comparator 605 to compare the pixels in a first pixel block of the current video frame (e.g. , the first) and a corresponding second pixel block of the preceding video frame (e.g., the second) against a sum of absolute differences criterion to determine whether the first pixel block is a static block. The first pixel block of the current video frame (e.g., the first) and the corresponding second pixel block of the preceding video frame (e.g., the second) are both located at the same frame location and on the same component plane video and thus correspond to each other. In the illustrated example of Figure 6, the block-pixel comparator 605 computes a sum of absolute differences between pixels in the first pixel block and corresponding pixels (e.g., at the same frame location) in the second pixel block. The block-pixel comparator 605 then compares the sum of the absolute differences to a threshold. If the sum of the absolute differences satisfies (e.g., is less than) the threshold, the block-pixel comparator 605 identifies the first pixel block of the current video frame (e.g., the first) as a static block. Otherwise, the pixel-per-block comparator 605 identifies the first pixel block of the current video frame (e.g., the first) as a non-static block.

[051] In some examples, the block pixel comparator 605 employs different thresholds for different video component planes. For example, the block-pixel comparator 605 may employ a first threshold when evaluating the sum of absolute differences for a pixel block in the luminance plane, and a different second threshold when evaluating the sum of absolute differences for a pixel block in one of the chrominance planes. By way of example, for a 16 x 16 pixel block, which contains 256 total pixels, the pixel per block comparator 605 may use a threshold of 3 per pixel for the luminance plane, producing a total threshold of 3 x 256 = 768, against which the sum of absolute differences must be compared. However, the pixel per block comparator 605 may use a threshold of 4 per pixel for each of the chrominance planes, yielding a total threshold of 4 x 256 = 1024, against which the sum of the absolute differences must be compared. Different values per pixel to calculate thresholds for use in the luminance and/or chrominance planes, and/or different thresholds on their input, could alternatively be used.

[052] The example static block criteria evaluator 410 of Figure 6 also includes an example edge map creator 610 to create an edge map for the current input video frame. In some examples, the edge map creator 610 creates separate edge maps for the different video component planes of the current input video frame. The edge map creator 610 may use any type or combination of edge mapping techniques to identify edges in the current input video frame. For example, the edge map creator 610 of the illustrated example applies horizontal and vertical Sobel operators to the different video component planes (e.g., luminance and chrominance planes) of the current input video frame. The resulting edge map determined by edge map creator 610 identifies whether each pixel in the current input video frame is part of a vertical edge, is part of a horizontal edge, is part of both a vertical edge and a horizontal edge. , not part of a border, etc.

[053] The example static block criteria evaluator 410 of Figure 6 further includes one or both of an example block edge counter 615 and an example block edge match evaluator 620 to use the ) edge map(s) created by edge map creator 610 to determine whether a given pixel block of the current input video frame is a static block. For example, the per-block edge counter 615 compares the pixels in the given pixel block of the current input video frame (e.g., for a given component video plane) against an edge count criterion to determine whether there is a sufficient number of edge pixels in the given pixel block to perform an accurate static block determination. For example, the per-block edge counter 615 may use the edge map created by the edge map creator 610 for a given video component plane to determine which pixels in the given pixel block for the given video component plane are associated with edges and thus considered to be edge pixels. The per-block edge counter 615 of the illustrated example then counts the number of edge pixels in the given pixel block and compares the number to a threshold. If the number of edge pixels satisfies (e.g., is greater than or equal to) the threshold, the per-block edge counter 615 indicates that a static block determination can be performed for the given pixel block for the given component plane. of video.

[054] However, if the number of edge pixels does not satisfy (e.g., is less than) the threshold, the per-block edge counter 615 indicates that a static block determination cannot be performed for the given pixel block to the given video component plane. For example, a pixel block containing motion blur due to large motion and/or containing noise (e.g. resulting from light source changes, camera/sensor imperfections, etc.) may have some edges and thus static detection performed on that pixel block may be unreliable. In some examples, the threshold used to evaluate the number of edge pixels is determined by dividing the number of pixels in a pixel block by a factor. By way of example, for a 16 x 16 pixel block, which contains 256 total pixels, the edge counter per block 615 may use a factor of 4 to produce a threshold of 256 / 4 = 64, against which the number of edge pixels in a pixel block must be compared. Different factors and/or techniques for determining the limit could alternatively be used.

[055] In the illustrated example of Figure 6, the block edge matching evaluator 620 compares the edge pixels in a first pixel block of the current video frame (e.g., the first) and the corresponding pixels in a second block of the preceding video frame (e.g., the second) against an edge matching criterion to determine whether the first pixel block is a static block. For example, the block edge match evaluator 620 may use the edge map created by the edge map creator 610 for a given video component plane to determine which pixels in the first pixel block of the current video frame (e.g., example, the first) (and for the given video component plane) are associated with edges and thus considered to be edge pixels. The tile edge matching evaluator 620 may also use the edge map to identify the edge orientation associated with each edge pixel in the first pixel block (e.g., horizontal, vertical, both horizontal and vertical, none, etc. ). The block edge matching evaluator 620 of the illustrated example then compares the edge pixels identified in the first pixel block of the current (e.g., the first) video frame (and for the given video component plane) against the corresponding pixels at the same locations in the preceding (e.g., the second) video frame (and for the given video component plane) to determine the number of pixel pairs that are not in edge correspondence (e.g., that do not are on both edges or that are on both edges but have different orientations).

[056] The example block edge correspondence evaluator 620 of Figure 6 further compares the number of divergent pixel pairs (or, in other words, the number of pixel pairs that are not in correspondence) with a threshold . If the number of divergent pixel pairs for the first pixel block of the current (e.g., the first) video frame (and for the given component video plane) satisfies (e.g., is less than or equal to) the threshold , the number of diverging edge pairs is small, and thus the block edge matching evaluator 620 identifies the first (e.g., the first) pixel block of the current video frame (and for the given video component plane video) as a static block. Otherwise, if the number of divergent edge pairs does not satisfy (e.g., is greater than) the threshold, the block edge match evaluator 620 identifies the first pixel block of the current video frame (e.g., the first) (and for the given video component plane) as a non-static block.

[057] In some examples, the threshold used to evaluate the number of divergent edge pairs is determined by dividing the number of edge pixels in a pixel block by a factor. By way of example, the block edge matching evaluator 620 may use a factor of 32 to divide the number of edge pixels in a pixel block to determine the threshold for evaluating the number of divergent edge pairs. As such, the threshold varies depending on the number of edge pixels in the pixel block that is examined. For a 16 x 6 pixel block that has 256 total pixels, the upper limit on such a limit could be 256 / 36 = 8. Thus, in such an example, if more than 8 edge pairs in the current and preceding pixel block have no match, then the current pixel block is identified as non-static. Different factors and/or techniques for determining the limit could alternatively be used.

[058] In the example illustrated in Figure 6, the static block criteria evaluator 410 includes an example evaluation combiner 625 for combining the results of evaluating the static block detection criteria (e.g., which corresponds to combining the results of static block detection obtained by one or more or all of the example block pixel comparator 605, the example block edge counter 615, and/or the example block edge matching evaluator 620 in the illustrated example, but could correspond to combining other groups of criteria in other examples). In some examples, the evaluation combiner 625 determines that a given pixel block in a given video component plane of a given input frame is a static block if all evaluated static block criteria indicate that the given pixel block is a static block. Otherwise, if any of the evaluated static block criteria indicate that the given pixel block is not a static block, the evaluation combinator 625 determines that the given pixel block is a non-static block. In other examples, the evaluation combiner 625 determines that a given pixel block in a given video component plane of a given input frame is a static block if the majority of the evaluated static block criteria indicate that the given pixel block is a static block. Otherwise, if the majority of the evaluated static block criteria indicate that the given pixel block is not a static block, the evaluation combinator 625 determines that the given pixel block is a non-static block. In still other examples, evaluation combiner 625 determines that a given pixel block in a given video component plane of a given input frame is a static block if any of the evaluated static block criteria indicate that the given block of pixel is a static block. Otherwise, if all evaluated static block criteria indicate that the given pixel block is not a static block, the evaluation combinator 625 determines that the given pixel block is a non-static block.

[059] Figures 7A and B illustrate example operations of the example static block criteria evaluator 410 of Figure 6. Figure 7A represents a first pixel block of a current video frame (e.g., the first) and the Figure 7B represents the corresponding second pixel block of the preceding video frame (e.g., the second). In the illustrated example of Figures 7A and B, the lighter shaded pixels correspond to the edge pixels identified by the example edge map creator 610. In an example operation, the edge counter per block 615 counts the number of pixels of edges (e.g., lightly shaded) in the first pixel block depicted in Figure 7A and determines that the number of edge pixels meets the threshold to perform static block determination. In a further example operation, the example block edge matching evaluator 620 determines that the number of divergent pixel pairs between the first pixel block depicted in Figure 7A and the second pixel block depicted in Figure 7B satisfies the threshold used to evaluate the number of divergent edge pairs. Correspondingly, in such an example, the block edge matching evaluator 620 determines that the first pixel block depicted in Figure 7A is a static block.

[060] An example implementation of the static block criteria adjuster 445 of Figure 4 is illustrated in Figure 8. As mentioned above, the static block criteria adjuster 445 can adjust the static block detection criteria by the static block criteria evaluator. example static block 410. In some examples, the static block criteria adjuster 445 causes different adjustments to the static block detection criteria to be applied when evaluating different pixel blocks of the current video frame (e.g., the first). that is being processed. In other examples, the static block criteria adjuster 445 causes the same adjustment(s) to be applied to evaluate all pixel blocks of the current video frame (e.g. , the first) that is being processed.

[061] Turning to Figure 8, the example static block criteria adjuster 445 illustrated therein includes an example phase plane correlator 805 for examining the correlation between the input video frame (e.g., current ) being processed and the preceding frame to determine whether regions of the input video frame correspond to motion or non-motion regions. In the illustrated example, the phase plane correlator 805 divides the pair of input (e.g., current) and preceding video frames for a given component video plane (also referred to as the given phase plane) into regions (e.g., example, such as regions of 512 x 256 pixels or some other pixel size). Then, for each region, the phase plane correlator 805 calculates the phase plane correlation between the input (e.g., current) video frame and the preceding frame in the given region. If the first (e.g., strongest) correlation peak for the given region is in the position corresponding to zero motion, then the phase plane correlator 805 of the illustrated example indicates that one or more of the static block detection criteria should be adjusted in order to declare the pixel blocks in the given region to be static blocks. If the second correlation peak (e.g., the second strongest) for the given region is in the position corresponding to zero motion, then the phase plane correlator 805 of the illustrated example leaves the static block detection criteria unchanged to evaluate the pixel blocks in the given region. If neither of the first two correlation peaks (e.g., the strongest peak and the second strongest peak) for the given region is in the position corresponding to zero motion, then the phase plane correlator 805 of the illustrated example indicates that a or more of the static block detection criteria must be adjusted in order to declare the pixel blocks in the given region to be non-static blocks.

[062] In some examples, the example static block criteria adjuster 445 of Figure 8 also includes an example static map hysteresis evaluator 810, which can examine previous static maps determined by the static region detector 115 and apply hysteresis or another feedback to adjust, if necessary, one or more of the static block detection criteria. For example, the static map hysteresis evaluator 810 may examine the input for a given pixel block location and/or the input or inputs for its nearby block locations in a previous static map determined by the static region detector 115. If the previous static map entry or entries for the given pixel block location and/or its neighboring block locations indicate that those location(s) were identified as being static blocks in the previous static map (e.g., that it corresponds to to the preceding video frame), then there is a strong possibility/probability that the given pixel block in the current video frame being processed is still a static block. Correspondingly, in such a case, the static map hysteresis evaluator 810 indicates that one or more of the static block detection criteria must be adjusted in order to declare the given pixel block in the current frame to be a static block. However, if, for a given pixel block in the current video frame, the given pixel block location and/or its nearby block locations were identified as being non-static blocks in the previous static map (e.g., corresponding to the frame video frame), then there is a strong possibility/probability that the given pixel block in the current video frame being processed is still a non-static block. Correspondingly, in such a case, the static map hysteresis evaluator 810 indicates that one or more of the static block detection criteria must be adjusted in order to declare the given pixel block in the current frame to be a non-static block.

[063] The example static block criteria adjuster 445 of Figure 8 further includes an example static block criteria adjustment specifier 815 to specify the adjustment(s), if any, to be performed on one or more of the static block detection criteria based on the results of the phase plane correlator 805 and/or the static map hysteresis evaluator 810. In some examples, to adjust a particular static block detection criterion in order to declaring the pixel blocks in the given region to be static blocks, the static block criteria adjustment specifier 815 adjusts the threshold of the particular static block detection criteria by some percentage value in a first direction. Conversely, in some examples, to adjust a particular static block detection criterion in order to declare the pixel blocks in the given region to be non-static blocks, the static block criteria adjustment specifier 815 adjusts the criteria threshold. particular static block detection by the same or different percentage value in a second opposite direction. For example, the static block criteria tuning specifier 815 may, in some examples, adjust (e.g., increase) the threshold used by the per-block pixel comparator 605 of Figure 6 by some percentage (e.g., 10%, 25 %, etc.) to nudge the pixel-by-block comparator 605 toward identifying pixel blocks in a given region as static blocks, and may adjust (e.g., decrease) the threshold by some percentage (e.g., 10% , 25%, etc.) to induce the block-pixel comparator 605 toward identifying pixel blocks in the given region as non-static blocks. Additionally or alternatively, in some examples, the static block criteria adjustment specifier 815 may adjust (e.g., increase) the threshold used by the per-block edge match evaluator 620 of Figure 6 by some percentage (e.g., 10% , 25%, etc.) to nudge the block edge matching evaluator 620 toward identifying pixel blocks in a given region as static blocks and may adjust (e.g., decrease) the threshold by some percentage (e.g. , 10%, 25%, etc.) to nudge the block edge matching evaluator 620 toward identifying pixel blocks in the given region as non-static blocks.

[064] An example implementation of the static map combiner 425 of Figure 4 is illustrated in Figure 9. As mentioned above, the example static map combiner 425 combines the different static maps for a given input video frame (e.g. , current) into a general static map that identifies the zero or more static pixel blocks in the given input video frame (e.g., current). In the example illustrated in Figure 9, the static map combiner 425 includes an example intra-component static map combiner 905 for combining multiple static maps that are associated with the same video component plane of the input (e.g., current) video frame. that is being processed. For example, for a given video component plane (e.g., the luminance plane, one of the chrominance planes, etc.), example video segmenter 405 may perform multiple segmentation iterations of the current video frame that is being processed, wherein the pixel blocks obtained from a first segmentation iteration partially overlap the pixel blocks obtained from a second segmentation iteration. The static block criteria evaluator 410 may then compare, for the given video component plane, the pixel blocks obtained for the current video frame from the first segmentation iteration with the corresponding pixel blocks obtained from of a corresponding first segmentation iteration of the preceding video frame to determine the static block(s) corresponding to the first segmentation iteration of the current video frame. Similarly, the static block criteria evaluator 410 may compare, for the given video component plane, the pixel blocks obtained from the second iteration of segmenting the video frame with corresponding pixel blocks obtained from a second iteration. corresponding segmentation iteration of the preceding video frame to determine the static block(s) corresponding to the second segmentation iteration of the current video frame. The static map creator 415 can then create separate static maps for each segmentation iteration, which respectively identify the static blocks detected in each segmentation iteration of the current video frame.

[065] In some such examples, the intracomponent static map combiner 905 combines the different static maps corresponding to the different segmentation iterations to form a composite static map for the given video component plane. In some examples, each entry in the composite static map for a given video component plane corresponds to a pixel subblock in the given video component plane. A pixel subblock corresponds to the overlapping pixel block region that is included in the pixel blocks of different segmentation iterations. For example, subblock 560 of Figure 5 corresponds to the overlapping pixel block region that is included in pixel blocks 510, 525, 535, and 550 of segmentation iterations 505, 520, 530, and 545, respectively. Correspondingly, the resolution of the composite static map will be better (e.g., higher resolution) than the individual static maps due to the fact that the sub-blocks in the composite map will be smaller than the pixel blocks in the individual static maps corresponding to different segmentation iterations.

[066] As a few examples, the intracomponent static map combiner 905 determines the value of an input for a given sub-block based on the values of some or all of the pixel blocks, across the different segmentation iterations, that contain the data. sub-block. For example, the intracomponent static map combiner 905 may be configured to set the value of the composite pixel map input for the given sub-block to be a value (e.g., a logical “1”) that identifies the sub-block. block as being a static block if all pixel blocks (across the different segmentation iterations) that contain the subblock have respective static map entries that identify the blocks as static blocks. Otherwise, if any of the pixel blocks containing the subblock have a respective map value that identifies the block as a non-static block, the intracomponent static map combiner 905 sets the value of the pixel map input composite for the given sub-block as a value (e.g., a logical “0”) that identifies the sub-block as being a non-static block. In other examples, the intracomponent static map combiner 905 sets the value of the composite pixel map input for the given subblock to be a value corresponding to a majority vote of the respective static map inputs for the pixel blocks ( through the different segmentation iterations) that contain the sub-block. In such examples, if the majority of pixel blocks (across the different segmentation iterations) that contain the given sub-block are identified as static blocks, the given pixel sub-block is also identified as a static block. Otherwise, if the majority of pixel blocks (across different segmentation iterations) that contain the given sub-block are identified as non-static blocks, the given pixel sub-block is also identified as a non-static block.

[067] Example static map combiner 425 also includes an example intra-component static map combiner 910 for combining multiple static maps that are associated with different video component planes of the input (e.g., current) video frame that is being processed. For example, as described above, the static map creator 415 of the illustrated example creates different static maps for the different video component planes (e.g., one luminance plane and two chrominance planes) of a current video frame. being processed, where each static map identifies the static blocks in the respective video component plane of the current video frame being processed. In such examples, the intra-component static map combiner 910 obtains the different static maps (e.g., which may be composite maps if the example intra-component static map combiner 905 is present) determined for the different video component planes of the frame. current video frame being processed and combines the individual static maps for the different video component planes into an overall static map for the current video frame.

[068] In some examples, the intracomponent static map combiner 910 is configured to set the value of the general pixel map input for the given pixel block to be a value (e.g., a logical “1”) that identifies the given pixel block as being a static block if all pixel blocks for the different video component planes corresponding to the given pixel block have respective static map entries that identify the blocks as static blocks. Otherwise, if any of the pixel blocks, in the different video component planes, corresponding to the given pixel block of interest have a respective map value that identifies the block as a non-static block, the intra-component static map combiner 910 of such examples define the value of the general pixel map input for the given pixel block to be a value (e.g., a logical “0”) that identifies the pixel block as being a non-static block. In other examples, the intracomponent static map combiner 910 sets the value of the overall pixel map input for the given pixel block of interest to be a value corresponding to a majority vote of the respective static map inputs for pixel blocks. from the different video component planes, corresponding to the given pixel block of interest. In such examples, the given pixel block of interest is defined as a static block if the majority of pixel blocks, from the different video component planes, corresponding to the given pixel block are identified as static blocks. Otherwise, the given pixel block of interest is defined as a non-static block if the majority of pixel blocks from the different video component planes corresponding to the given pixel block are identified as non-static blocks.

[069] Figure 10 illustrates example operation results that can be achieved by the example video processing system 100 that employs the example static region detector 115 of Figure 1. In particular, Figure 10 illustrates the interpolation results example frame rate that can be achieved when performing frame rate upconversion using block-based static region detection as implemented by static region detector 115 of Figure 1. Figure 10 depicts an example frame 1005 corresponding to an example interpolated frame determined by the frame rate upconverter 120 without using any static region information provided by the static region detector 115. An example frame 1010 depicted in Figure 10 corresponds to an example interpolated frame determined by the framerate upconverter 1010. frame rate 120 with static region information determined by static region detector 115 under a first example configuration. In the first example configuration, the static block criteria evaluator 410 of the static region detector 115 includes the per-block pixel comparator 605 and the per-block edge counter 615, but not the per-block edge matching evaluator 620. In addition Furthermore, in the first example configuration, the static region detector 115 does not include the static block criteria adjuster 445.

[070] An example frame 1015 depicted in Figure 10 corresponds to an example interpolated frame determined by frame rate upconverter 120 with static region information determined by static region detector 115 under a second example configuration. In the second example configuration, the static block criteria evaluator 410 of the static region detector 115 includes the per-block pixel comparator 605, the per-block edge counter 615, and not the per-block edge matching evaluator 620. In addition Furthermore, in the second example configuration, the static region detector 115 includes the static block criteria adjuster 445. The lightly shaded regions in the example frame 1020 of Figure 10 correspond to the static regions identified by the static region detector 115 under the second example configuration.

[071] Although example modes for implementing example video processing system 100 and, more specifically, example static region detector 115 are illustrated in Figures 1 to 10, one or more of the elements, processes and/or devices illustrated in Figures 1 to 10 may be combined, divided, reorganized, omitted, eliminated and/or implemented in any other way. Additionally, example frame rate upconverter 120, example motion estimator 125, example video segmenter 405, example static block criteria evaluator 410, example static map creator 415, example example static map store 420, example static map combiner 425, example media filter 430, example static region identifier 435, example static region checker 440, example static block criteria adjuster example 445, the example tile pixel comparator 605, the example edgemap creator 610, the example tile edge counter 615, the example tile edge match evaluator 620, the evaluation combiner example 625, example phase plane correlator 805, example static map hysteresis evaluator 810, example static block criteria adjustment specifier 815, example intracomponent static map combiner 905, example Example intracomponent static map combiner 910 and/or, more generally, example static region detector 115 and/or example video processing system 100 of Figures 1 to 10 may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, any of example frame rate upconverter 120, example motion estimator 125, example video segmenter 405, example static block criteria evaluator 410, example map creator example static map 415, the example static map store 420, the example static map combiner 425, the example media filter 430, the example static region identifier 435, the example static region checker 440, the example static tile criteria adjuster 445, example tile per pixel comparator 605, example edge map creator 610, example per tile edge counter 615, example per tile edge match evaluator 620, example evaluation combiner 625, example phase plane correlator 805, example static map hysteresis evaluator 810, example static block criteria adjustment specifier 815, example static map combiner example intracomponent static map combiner 905, the example intracomponent static map combiner 910 and/or, more generally, the example static region detector 115 and/or the example video processing system 100 could be deployed by one or more analog or digital circuit(s), logic circuits, programmable processor(s), application-specific integrated circuit(s) (ASIC(s)), logic device(s) programmable logic device(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)). When reading any of the apparatus or system claims of this patent to encompass a purely software and/or firmware implementation, at least one of example video processing system 100, example static region detector 115, upconverter example framerate 120, example motion estimator 125, example video segmenter 405, example static tile criteria evaluator 410, example static map creator 415, example static map store example 420, example static map combiner 425, example media filter 430, example static region identifier 435, example static region checker 440, example static block criteria adjuster 445, example example per-tile pixel comparator 605, the example edge map creator 610, the example per-tile edge counter 615, the example per-tile edge match evaluator 620, the example evaluation combiner 625, the example phase plane correlator 805, example static map hysteresis evaluator 810, example static block criteria adjustment specifier 815, example intracomponent static map combiner 905, and/or the map combiner static intracomponent example 910 is/are expressly defined herein as including a computer-readable tangible storage device or storage disk, such as a memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-ray, etc. which stores the software and/or firmware. Furthermore, the example video processing system 100 and/or the example static region detector 115 of Figures 1 to 10 may include one or more elements, processes and/or devices in addition to those illustrated in Figures 1 to 10, or rather than the same, and/or may include more than one of any or all of the illustrated elements, processes and devices.

[072] Flowcharts representative of example machine-readable instructions for implementing example video processing system 100, example static region detector 115, example frame rate upconverter 120, example motion estimator example 125, the example video slicer 405, the example static block criteria evaluator 410, the example static map creator 415, the example static map store 420, the example static map combiner 425, the example example media filter 430, example static region identifier 435, example static region checker 440, example static tile criteria adjuster 445, example tile pixel comparator 605, map creator example edge matcher 610, the example block edge counter 615, the example block edge matching evaluator 620, the example evaluation combiner 625, the example phase plane correlator 805, the hysteresis evaluator example static map combiner 810, example static block criteria tuning specifier 815, example intracomponent static map combiner 905 and/or example intracomponent static map combiner 910 are shown in Figures 11 to 14. In these examples, the machine-readable instructions comprise one or more programs for execution by a processor, such as the processor 1512 shown in example processor platform 1500 discussed below in connection with Figure 15. The one or more programs, or portion ( s) thereof, may be embodied in stored software and a computer-readable tangible storage medium, such as a CD-ROM, a floppy disk, a hard drive, a digital versatile disc (DVD), a Blu-ray™ disc, or a memory associated with processor 1512, the entire program(s) and/or portions thereof could alternatively be executed by a device other than processor 1512 and/or incorporated into dedicated firmware or hardware (e.g., implemented by an ASIC, a PLD, an FPLD, a discrete logic, etc.). Additionally, one or more of the machine-readable instructions represented by the flow charts in Figures 11 through 14 can be implemented manually. Furthermore, although the example program(s) are described with reference to the flowcharts illustrated in Figures 11 to 14, many other methods for implementing the example video processing system 100, the example static region 115, example frame rate upconverter 120, example motion estimator 125, example video segmenter 405, example static block criteria evaluator 410, example static map creator example 415, example static map store 420, example static map combiner 425, example media filter 430, example static region identifier 435, example static region checker 440, example static region adjuster example static block criteria 445, the example block pixel comparator 605, the example edge map creator 610, the example per block edge counter 615, the example per block edge match evaluator 620, example evaluation combiner 625, example phase plane correlator 805, example static map hysteresis evaluator 810, example static block criteria tuning specifier 815, example example 905 and/or the intracomponent static map combiner of example 910 may alternatively be used. For example, with reference to the flowcharts illustrated in Figures 11 to 14, the order of execution of the blocks may be changed and/or some of the described blocks may be altered, deleted, combined and/or subdivided into multiple blocks.

[073] As mentioned above, the example processes of Figures 11 to 14 can be implemented using encoded instructions (e.g., computer-readable and/or machine-readable instructions) stored on a tangible computer-readable storage medium, such such as hard disk drives, flash memory, read-only memory (ROM), compact disk (CD), digital versatile disk (DVD), provisional temporary storage, random access memory (RAM), and /or any other storage device or storage disk on which information is stored for any duration (e.g., for extended periods of time, permanently, briefly, for temporary memory storage and/or temporary provision storage of the information) . As used herein, the term computer-readable tangible storage medium is expressly defined as including any type of computer-readable storage device and/or storage disk and excluding propagating signals and excluding transmission media. As used herein, “computer-readable tangible storage medium” and “machine-readable tangible storage medium” are used interchangeably. Additionally or alternatively, the example processes of Figures 11 to 14 may be implemented with the use of encoded instructions (e.g., computer- and/or machine-readable instructions) stored on a non-transitory computer- and/or machine-readable medium, such such as a hard disk drive, a flash memory, a ROM, a CD, a DVD, a cache, a RAM and/or any other storage device or storage disk on which information is stored for any duration (e.g. extended periods of time, permanently, for brief moments, for temporary memory storage and/or caching of information). As used herein, the term non-transitory computer-readable medium is expressly defined as including any type of computer-readable storage device and/or storage disk and excluding propagating signals and excluding transmission media. As used herein, when the phrase “at least” is used as the transitional term in a preamble to a claim, the same is open-ended in the same manner as the term “comprising” is open-ended. Furthermore, as used herein, the terms “computer readable” and “machine readable” are considered equivalent unless otherwise indicated.

[074] An example program 1100 that can be executed to implement the example static region detector 115 of Figures 1 and/or 4 is represented by the flowchart shown in Figure 11. The example program 1100 can be executed by the region detector static region 115 to perform block-based static region detection as disclosed herein. With reference to the preceding figures and associated written descriptions, the example program 1100 of Figure 11 begins execution at block 1105, in which the static region detector 115 obtains a current video frame from the input video sequence 105 for processing, as per described above. In block 1110, the example video segmenter 405 of the static region detector 115 segments the different video component planes (e.g., the luminance plane and the two chrominance planes) of the current video frame into pixel blocks, as described above.

[075] In block 1115, the static region detector 115 evaluates, for each video component plane, the pixel blocks obtained in block 1100 for the current video frame and corresponding pixel blocks for a preceding video frame against a or more static block detection criteria to identify the static block(s), if any, in each video component plane of the current frame, as described above. As further described above, in block 1115 the static region detector 115 uses these evaluation results to determine static maps for the different video component planes of the current video frame. The static map for a given video component plane includes entries for each pixel block in the given video component plane of the current video frame, and the entry for particular pixel blocks identifies the pixel block as a static block or a non-static block. An example program that can implement processing in block 1115 is illustrated in Figure 12, which is described in more detail below.

[076] In block 1120, static region detector 115 determines whether multiple overlapping segmentation iterations of the current video frame, as described above, are supported. If multiple segmentation iterations, with overlap, are supported (block 1120), then, in block 1125, the static region detector 115 determines whether all iterations to segment the current video frame are complete. If the segmentation of the current video frame is not complete (block 1125), then in block 1130, the video segmenter 405 of the static region detector 115 is configured with segmentation offset to be used for the next segmentation iteration. Processing then returns to blocks 1110, and the blocks subsequent thereto, where the current video frame is segmented based on the configured offset, and the static block(s), if any, are (are) detected in the resulting pixel blocks as described above.

[077] In block 1135, example static map combiner 425 of static region detector 115 combines the individual static maps determined for the current video frame over multiple video component planes and/or over multiple different video offsets. segmentation to determine a general static map that identifies the static block(s), if any, in the current video frame, as described above. An example program that can implement processing in block 1135 is illustrated in Figure 13, which is described in more detail below. The overall static map determined in block 1135 may then be further processed by static region detector 115 to identify the static region(s), if any, of the current video frame, as described above.

[078] An example program 1115P that can be executed to implement the example static block criteria evaluator 410 of Figures 4 and/or 6, and/or the example static map creator 415 of Figure 4, and/or which can be used to implement processing in block 1115 of Figure 11, is represented by the flowchart shown in Figure 12. With reference to the previous figures and associated written descriptions, the example program 1115P of Figure 12 begins execution in block 1205, at that the static block criteria evaluator 410 and the static map maker 415 of the static region detector 115 are configured to perform static block detection for a given video component plane (e.g., the luminance plane or one of the chrominance planes) of the current video frame being processed. In block 1210, the static block criteria evaluator 410 compares, based on the static block detection criteria, corresponding pixel blocks in the given video component plane of the current video frame and the preceding video frame to identify the ( s) static block(s), if any, in the current video frame. For example, the static block criteria evaluator 410 may use one, some, or all of the example block pixel comparator 605, the sample block edge counter 615, and/or the sample block edge match evaluator 605. example 620, which are described above, to evaluate the static block detection criteria in block 1210.

[079] In block 1215, example evaluation combiner 625 of static block criteria evaluator 410 combines, as described above, the results of evaluating the static block detection criteria in block 1210 to determine the block(s) s) static(s), if any, in the given component plane of the current video frame. In block 1220, static map creator 415 creates a static map for the given video component plane of the current video frame. As described above, the static map includes the respective entries for each pixel block in the given video component plane of the current video frame, and the static map values are set to indicate which pixel blocks, if any, are static blocks. and which pixel blocks, if any, are non-static blocks. In block 1225, static region detector 115 causes processing to continue until all video component planes of the current video frame have been processed. In block 1230, the static map creator 415 outputs and/or stores respective static maps determined for the different video component planes of the current video frame.

[080] An example program 1135P that can be executed to implement the example static map combiner 425 of Figures 4 and/or 9, and/or that can be used to implement processing in block 1135 of Figure 11, is depicted by the flowchart shown in Figure 13. Referring to the preceding figures and associated descriptions, the example program 1135P of Figure 13 begins execution at block 1305, wherein the static map combiner 425 of the static region detector 115 determines whether multiple iterations overlay segmentation of the current video frame as described above is supported. If multiple segmentation iterations, with overlap, are supported (block 1305), then, in block 1310, example intracomponent static map combiner 905 of example static map combiner 425 is configured to perform intracomponent static map combining for a given video component plane (e.g., the luminance plane or one of the chrominance planes) of the current video frame being processed. In block 1315, intracomponent static map combiner 905 performs intracomponent static map combining of different static maps determined for the given video component plane of the current video frame. As described above, the different static maps correspond to different segmentations of the given video component plane of the current video with different segmentation offsets, and each static map identifies the static block(s), if any, identifies (s) for a particular targeting offset. At block 1315, the result of the intra-component static map combination is a single composite static map that identifies the static block(s), if any, in the given video component plane of the current video frame that is being processed.

[081] In block 1320, example intracomponent static map combiner 905 causes processing to continue until intracomponent static map combining for all video component planes of the current video frame is complete. In block 1325, example intra-component static map combiner 910 of static map combiner 425 performs intra-component static map combining of the different static maps, which may or may not be composite static maps, for the different video component planes of the frame. current video frame to determine a general static map for the current video frame, as described above. The overall static map identifies the static block(s), if any, in the current video frame being processed.

[082] An example program 1400 that can be executed to implement the example static block criteria adjuster 445 of Figures 4 and/or 8 is represented by the flowchart shown in Figure 14. With reference to the preceding figures and associated written descriptions, The example program 1400 of Figure 14 begins execution at block 1405, in which the static block criteria adjuster 445 of the static region detector 115 is configured to evaluate a given video component plane (e.g., the luminance plane or one of the chroma planes) of the current video frame being processed. In block 1410, the example phase plane correlator 805 of the static block criteria adjuster 445 compares the region(s) of the current and preceding video frames of the input video sequence 105 to determine the adjustment(s), if any, to be made to one or more of the static block detection criteria evaluated by the static block criteria evaluator 410, as described above. In block 1415, example static map hysteresis evaluator 810 of static block criteria adjuster 445 examines one or more previous static maps determined for one or more previous video frames in the input video sequence 105 to determine the ) adjustment(s), if any, to be made to one or more static block detection criteria evaluated by the static block criteria evaluator 410, as described above. In block 1420, static block criteria adjuster 445 causes processing to continue until evaluation of all video component planes is complete. Then, in block 1425, example static block criteria adjustment specifier 815 applies, as described above, the adjustment(s), if any, to be made to one or more of the detection criteria. static block based on the results obtained in blocks 1410 and/or 1415.

[083] Figure 15 is a block diagram of an example processor platform 1500 that has the ability to execute the instructions of Figures 11 to 14 to implement the example video processing system 100, the example static region detector 115, the example frame rate upconverter 120, the example motion estimator 125, the example video segmenter 405, the example static block criteria evaluator 410, the example static map creator 415, the example static map store 420, example static map combiner 425, example media filter 430, example static region identifier 435, example static region checker 440, example static block criteria adjuster example 445, the example tile pixel comparator 605, the example edgemap creator 610, the example tile edge counter 615, the example tile edge match evaluator 620, the evaluation combiner example 625, example phase plane correlator 805, example static map hysteresis evaluator 810, example static block criteria adjustment specifier 815, example intracomponent static map combiner 905, and/or or the example intracomponent static map combiner 910 of Figures 11 through 14. The processor platform 1500 may be, for example, a server, a personal computer, a mobile device (e.g., a cell phone, a smartphone-type phone, , a tablet-type computer such as an iPadTM), a personal digital assistant (PDA), an Internet-connected device, a DVD player, a CD player, a digital video recorder, a Blu-ray player, a game console, personal video recorder, set-top box, digital camera, or any other type of computing device.

[084] The processor platform 1500 of the illustrated example includes a processor 1512. The processor 1512 of the illustrated example is hardware. For example, processor 1512 may be implemented by one or more integrated circuits, logic circuits, microprocessors, or controllers of any desired family or manufacturer.

[085] The processor 1512 of the illustrated example includes a local memory 1513 (e.g., a cache). The processor 1512 of the illustrated example is in communication with a main memory that includes a volatile memory 1514 and a non-volatile memory 1516 via a link 1518. The link 1518 may be implemented by a bus, one or more point-to-point connections, etc., or a combination thereof. The volatile memory 1514 may be deployed by Synchronized Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM), and/or any other type of random access memory device. The non-volatile memory 1516 may be implemented by flash memory and/or any other desired type of memory device. Access to main memory 1514, 1516 is controlled by a memory controller.

[086] The processor platform 1500 of the illustrated example also includes an interface circuit 1520. The interface circuit 1520 can be implemented by any type of interface standard, such as an Ethernet interface, a universal serial bus (USB) and/or or a PCI express interface.

[087] In the illustrated example, one or more input devices 1522 are connected to the interface circuit 1520. The input device(s) 1522 allows a user to enter data and commands into the processor 1512. The device(s) input(s) may be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touch screen, a trackpad, a trackball, a trackbar (such as an isopoint), a voice recognition system and/or any other interface between human and machine. Additionally, many systems, such as processor platform 1500, may allow the user to control the computer system and provide data to the computer using physical gestures, such as, but not limited to, hand or body movements. , facial expressions and face recognition.

[088] One or more output devices 1524 are also connected to the interface circuit 1520 of the illustrated example. The output devices 1524 may be implemented, for example, by display devices (e.g., a light-emitting diode (LED), an organic light-emitting diode (OLED), a liquid crystal display, a cathode rays (CRT), a touch screen, a tactile output device, a light-emitting diode (LED), a printer, and/or speakers). The interface circuit 1520 of the illustrated example thus typically includes a graphics card, a graphics chip, or a graphics processor.

[089] The interface circuit 1520 of the illustrated example also includes a communication device, such as a transmitter, a receiver, a transceiver, a modem and/or a network interface card to facilitate data exchange with external machines ( e.g., computing devices of any type) via a network 1526 (e.g., an Ethernet connection, a digital subscriber line (DSL), a telephone line, a coaxial cable, a cellular telephone system, etc. ).

[090] The processor platform 1500 of the illustrated example also includes one or more mass storage devices 1528 for storing software and/or data. Examples of such mass storage devices 1528 include floppy disk drives, hard disk drives, compact disk drives, Blu-ray disk drives, RAID (redundant array of independent disks) systems, and digital versatile disk (DVD) drives. ).

[091] Coded instructions 1532 corresponding to the instructions of Figures 11 to 14 may be stored in mass storage devices 1528, volatile memory 1514, non-volatile memory 1516, local memory 1513 and/or a readable tangible storage medium by removable computer, such as a CD or DVD 1536.

[092] The following additional examples include such a method for performing block-based static region detection for video processing, means for performing block-based static region detection for video processing, at least one machine-readable medium that includes instructions that, when performed by a machine cause the machine to perform block-based static region detection for video processing, an apparatus and/or a system for implementing block-based static region detection for video processing that are disclosed in this document.

[093] Example 1 is a video processing method that includes segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks. The method of example 1 also includes processing, with a processor, the first plurality of pixel blocks and a second plurality of pixel blocks corresponding to a previous second frame of the video sequence to create, based on a first criterion, a map that identifies one or more static pixel blocks in the first plurality of pixel blocks. The method of example 1 further includes identifying, based on the map, a static region in the first frame of the video sequence.

[094] Example 2 includes the subject matter of example 1, wherein the processing includes evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on the first criterion to determine a first static block identification result, evaluate the first plurality of pixel blocks and the second plurality of pixel blocks based on a second criterion to determine a second static block identification result and combine the first and second static block identification results to create the map that identifies the one or more static pixel blocks in the first plurality of pixel blocks.

[095] Example 3 includes the subject matter of example 1, wherein the first criterion includes a sum of absolute differences criterion, and the processing includes computing a sum of absolute differences between pixels in a first pixel block of the first plurality of blocks of pixel and corresponding pixels in a second corresponding pixel block of the second plurality of pixel blocks and determining whether the first pixel block is a static block by comparing the sum of absolute differences to a threshold.

[096] Example 4 includes the subject matter of example 1, wherein the first criterion includes an edge count criterion, and the processing includes determining an edge map that identifies the edges in the first frame of the video sequence, counting a number of pixels in a first pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map and determining whether the first pixel block is a static block by comparing the number to a threshold.

[097] Example 5 includes the subject matter of example 1, wherein the first criterion includes an edge matching criterion, and the processing includes determining a first edge map that identifies edges in the first frame of the video sequence, identifying the first edge pixels in a first pixel block of the first plurality of pixel blocks, wherein the first edge pixels are associated with the edges identified in the first edge map, determine a number of first edge pixels that have no edge correspondence with the respective second edge pixels in a corresponding second pixel block of the second plurality of pixel blocks, wherein two edge pixels are edge matched when the two edge pixels have the same frame location and are associated with the same orientation edge and determine whether the first pixel block is a static block by comparing the number to a threshold.

[098] Example 6 includes the subject matter of example 1, wherein the first frame has multiple video components, the first plurality of pixel blocks is associated with a video component foreground, the map is a first map and includes , further, segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a video component background different from the video component foreground. Example 6 also includes processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the video component background of the previous second frame of the video sequence to create, based on the first criterion, a second map that identifies one or more static pixel blocks in the third plurality of pixel blocks. Example 6 further includes identifying, based on the first and second maps, the static region in the first frame of the video sequence.

[099] Example 7 includes the subject matter of example 6, wherein identifying, based on the first and second maps, the static region in the first frame of the video sequence includes combining the first map and the second map to determine an overall map that identifies one or more static pixel blocks in the first frame of the video sequence.

[0100] Example 8 includes the material of example 1, in which the map is a first map and also includes. Example 8 also includes segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks, wherein those of the third plurality of pixel blocks partially overlap those of the first plurality of blocks. Example 8 also includes processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the previous second frame of the video sequence to create, based on the first criterion, a second map that identifies one or more static blocks of pixel in the third plurality of pixel blocks, wherein those of the fourth plurality of pixel blocks partially overlap those of the second plurality of blocks. Example 8 further includes identifying, based on the first and second maps, the static region in the first frame of the video sequence.

[0101] Example 9 includes the subject matter of example 8, wherein identifying, based on the first and second maps, the static region in the first frame of the video sequence includes combining the first map and the second map to determine an overall map that identifies one or more static pixel sub-blocks in the first frame of the video sequence, wherein a first sub-block in the first frame is included in a first block of the first plurality of pixel blocks and a first block of the third plurality of blocks, where the overall map has a better resolution than the first and second blocks. Example 9 also includes identifying the static region in the first frame of the video sequence based on the overall map.

[0102] Example 10 includes the subject matter of example 1, wherein the map is a first map and further includes adjusting the first criterion based on at least one of (1) a correlation determined between the first and second frames of the video sequence or (2) evaluating a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence.

[0103] Example 11 is a method as defined in any one of claims 1 to 5, wherein the map is a first map and further includes adjusting the first criterion based on at least one of (1) a correlation determined between the first and second frames of the video sequence or (2) evaluating a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence.

[0104] Example 12 is at least one machine-readable tangible storage medium that includes machine-readable instructions that, when executed, cause a machine to at least segment the pixels in a first frame of a video sequence into a first plurality of pixel blocks. The instructions of example 12, when executed, also cause the machine to at least process the first plurality of pixel blocks and a second plurality of pixel blocks corresponding to a previous second frame of the video sequence to create, based on a first criterion , a map that identifies one or more static pixel blocks in the first plurality of pixel blocks. The instructions in example 12, when executed, also cause the machine to at least identify, based on the map, a static region in the first frame of the video sequence.

[0105] Example 13 includes the subject matter of example 12, wherein the machine-readable instructions, when executed, further cause the machine to evaluate the first plurality of pixel blocks and the second plurality of pixel blocks based on the first criterion for determining a first static block identification result, evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on a second criterion for determining a second static block identification result, and combining the first and the second static block identification results to create the map that identifies the one or more static pixel blocks in the first plurality of pixel blocks.

[0106] Example 14 includes the subject matter of example 12, in which the first criterion includes a sum of absolute differences criterion, and the machine-readable instructions, when executed, further cause the machine to compute a sum of absolute differences between pixels in a first pixel block of the first plurality of pixel blocks and corresponding pixels in a second corresponding pixel block of the second plurality of pixel blocks and determining whether the first pixel block is a static block by comparing the sum of differences absolute to a limit.

[0107] Example 15 includes the subject matter of example 12, wherein the first criterion includes an edge count criterion, and the machine-readable instructions, when executed, further cause the machine to determine an edge map that identifies the edges in the first frame of the video sequence, count a number of pixels in a first pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map, and determine whether the first pixel block is a static block by comparing the number to a limit.

[0108] Example 16 includes the subject matter of example 12, wherein the first criterion includes an edge matching criterion, and the machine-readable instructions, when executed, further cause the machine to determine a first edge map that identifies edges in the first frame of the video sequence, identify the first edge pixels in a first pixel block of the first plurality of pixel blocks, wherein the first edge pixels are associated with the edges identified in the first edge map, determine a number of first edge pixels that do not have edge correspondence with respective second edge pixels in a corresponding second pixel block of the second plurality of pixel blocks, wherein the two edge pixels have edge correspondence when the two edge pixels have the same frame location and are associated with the same edge orientation, and determine whether the first pixel block is a static block by comparing the number to a threshold.

[0109] Example 17 includes the subject matter of example 12, wherein the first frame has multiple video components, the first plurality of pixel blocks is associated with a video component foreground, the map is a first map, and the machine-readable instructions, when executed, further cause the machine to segment the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a component video background different from the component video foreground , processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the video component background of the previous second frame of the video sequence to create, based on the first criteria, a second map that identifies one or more static pixel blocks in the third plurality of pixel blocks, and identifying, based on the first and second maps, the static region in the first frame of the video sequence.

[0110] Example 18 includes the subject matter of example 17, wherein the machine-readable instructions, when executed, further cause the machine to combine the first map and the second map to determine an overall map that identifies one or more static blocks of pixel in the first frame of the video sequence.

[0111] Example 19 includes the subject matter of example 12, wherein the map is a first map, and the machine-readable instructions, when executed, further cause the machine to segment the pixels in the first frame of the video sequence into a third plurality of pixel blocks, wherein those of the third plurality of pixel blocks partially overlap those of the first plurality of blocks, processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the previous second frame of the sequence of video to create, based on the first criterion, a second map that identifies one or more static pixel blocks in the third plurality of pixel blocks, wherein those in the fourth plurality of pixel blocks partially overlap with those in the second plurality of blocks , and identify, based on the first and second maps, the static region in the first frame of the video sequence.

[0112] Example 20 includes the subject matter of example 19, wherein the machine-readable instructions, when executed, further cause the machine to combine the first map and the second map to determine an overall map that identifies one or more sub-maps. static pixel blocks in the first frame of the video sequence, wherein a first sub-block in the first frame is included in a first block of the first plurality of pixel blocks and a first block of the third plurality of blocks, wherein the general map has better resolution than the first and second blocks, and identify the static region in the first frame of the video sequence based on the overall map.

[0113] Example 21 includes the subject matter of example 12, wherein the map is a first map, and the machine-readable instructions, when executed, further cause the machine to adjust the first criterion based on at least one of (1 ) a determined correlation between the first and second frames of the video sequence or (2) evaluation of a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence .

[0114] Example 22 includes the example subject matter of any of examples 12 to 16, wherein the map is a first map, and the machine-readable instructions, when executed, further cause the machine to adjust the first criterion based on in at least one of (1) a determined correlation between the first and second frames of the video sequence or (2) evaluation of a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the previous second frame of the video sequence.

[0115] Example 23 is at least one machine-readable tangible storage medium that includes machine-readable instructions that, when executed, cause a machine to perform a method, as defined in any of examples 1 to 11.

[0116] Example 24 is a video processing apparatus that includes a segmenter for segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks. The apparatus of example 24 also includes an evaluator for evaluating the first plurality of pixel blocks and a second plurality of pixel blocks corresponding to a second frame of the video sequence preceding the first frame based on a first criterion for determining one or more static pixel blocks in the first plurality of pixel blocks. The apparatus of example 24 further includes a map creator for creating a map that identifies the one or more static pixel blocks determined by the evaluator to be in the first plurality of pixel blocks. The apparatus of example 24 further includes an identifier for identifying, based on the map, a static region in the first frame of the video sequence.

[0117] Example 25 includes the subject matter of example 24 wherein the evaluator is to evaluate the first plurality of pixel blocks and the second plurality of pixel blocks based on the first criterion to determine a first static block identification result, and evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on a second criterion to determine a second static block identification result. In example 25, the map creator is to combine the first and second static block identification results to create the map that identifies the one or more static pixel blocks in the first plurality of pixel blocks.

[0118] Example 26 includes the subject matter of example 24, wherein the first criterion includes a sum of absolute differences criterion, and the evaluator is to compute a sum of absolute differences between pixels in a first pixel block of the first plurality of pixel blocks and corresponding pixels into a second corresponding pixel block of the second plurality of pixel blocks and determining whether the first pixel block is a static block by comparing the sum of absolute differences to a threshold.

[0119] Example 27 includes the subject matter of example 24, wherein the first criterion includes an edge count criterion, and the evaluator is to determine an edge map that identifies the edges in the first frame of the video sequence, count a number of pixels in a first pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map and determining whether the first pixel block is a static block by comparing the number to a threshold.

[0120] Example 28 includes the subject matter of example 24, wherein the first criterion includes an edge matching criterion, and the evaluator is to determine a first edge map that identifies edges in the first frame of the video sequence, identify the first edge pixels in a first pixel block of the first plurality of pixel blocks, wherein the first edge pixels are associated with the edges identified in the first edge map, determine a number of first edge pixels that have no edge correspondence with respective second edge pixels in a corresponding second pixel block of the second plurality of pixel blocks, wherein two edge pixels have edge correspondence when the two edge pixels have the same frame location and are associated with the same edge orientation and determine whether the first pixel block is a static block by comparing the number to a threshold.

[0121] Example 29 includes the subject matter of example 24, wherein the first frame has multiple video components, the first plurality of pixel blocks is associated with a video component foreground, the map is a first map, and the segmenter is further for segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a video component background different from the video component foreground. In example 29, the evaluator is further to evaluate the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the video component background of the previous second frame of the video sequence, based on the first criterion. to determine one or more static pixel blocks in the third plurality of pixel blocks. In example 29, the map creator is further to create a second map that identifies the one or more static pixel blocks determined by the evaluator to be in the third plurality of pixel blocks. In example 29, the identifier is to identify, based on the first and second maps, the static region in the first frame of the video sequence.

[0122] Example 30 includes the subject matter of example 29 and further includes a map combiner for combining the first map and the second map to determine an overall map that identifies one or more static pixel blocks in the first frame of the sequence. video.

[0123] Example 31 includes the subject matter of example 24, wherein the map is a first map, and the segmenter is further for segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks, in that those of the third plurality of pixel blocks partially overlap those of the first plurality of blocks. In example 31, the evaluator is to evaluate the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the previous second frame of the video sequence, based on the first criterion, to determine one or more static pixel blocks in the third plurality of pixel blocks, wherein those of the fourth plurality of pixel blocks partially overlap those of the second plurality of blocks. In example 31, the map creator is further to create a second map that identifies the one or more static pixel blocks determined by the evaluator to be in the third plurality of pixel blocks. In example 31, the identifier is further to identify, based on the first and second maps, the static region in the first frame of the video sequence.

[0124] Example 32 includes the subject matter of example 31 and further includes a map combiner for combining the first map and the second map to determine an overall map that identifies one or more static pixel sub-blocks in the first frame of the video sequence, wherein a first sub-block in the first frame is included in a first block of the first plurality of pixel blocks and a first block of the third plurality of blocks, wherein the overall map has better resolution than the first and the second blocks. In example 32, the identifier is to identify the static region in the first frame of the video sequence based on the overall map.

[0125] Example 33 includes the subject matter of example 24, wherein the map is a first map and further includes a criteria adjuster for adjusting the first criterion based on at least one of (1) a correlation determined between the first and second frames of the video sequence or (2) evaluating a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence.

[0126] Example 34 includes the subject matter of any of examples 24 to 28, wherein the map is a first map and further includes a criteria adjuster for adjusting the first criterion based on at least one of (1) a determined correlation between the first and second frames of the video sequence or (2) evaluation of a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence.

[0127] Example 35 is an apparatus that includes a processor configured to perform a method as defined in any of examples 1 to 11.

[0128] Example 36 is a video processing system that includes means for segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks. The system of example 36 also includes means for processing the first plurality of pixel blocks and a second plurality of pixel blocks corresponding to a previous second frame of the video sequence to create, based on a first criterion, a map that identifies a or more static pixel blocks in the first plurality of pixel blocks. The system of example 36 further includes means for identifying, based on the map, a static region in the first frame of the video sequence.

[0129] Example 37 includes the subject matter of example 36, wherein the processing means includes means for evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on the first criterion to determine a first identification result of static block, means for evaluating the first plurality of pixel blocks and the second plurality of pixel blocks based on a second criterion for determining a second static block identification result, and means for combining the first and second identification results of static block to create the map that identifies the one or more static pixel blocks in the first plurality of pixel blocks.

[0130] Example 38 includes the subject matter of example 36, wherein the first criterion includes a sum of absolute differences criterion, and the processing means includes means for computing a sum of absolute differences between pixels in a first pixel block of the first plurality of pixel blocks and corresponding pixels in a second corresponding pixel block of the second plurality of pixel blocks, means for determining whether the first pixel block is a static block by comparing the sum of absolute differences to a threshold.

[0131] Example 39 includes the subject matter of example 36, wherein the first criterion includes an edge count criterion, and the processing means includes means for determining an edge map that identifies the edges in the first frame of the video sequence , means for counting a number of pixels in a first pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map, and means for determining whether the first pixel block is a static block by comparing the number to a limit.

[0132] Example 40 includes the subject matter of example 36, wherein the first criterion includes an edge matching criterion, and the processing means includes means for determining a first edge map that identifies edges in the first frame of the video sequence. , means for identifying the first edge pixels in a first pixel block of the first plurality of pixel blocks, wherein the first edge pixels are associated with the edges identified in the first edge map, means for determining a number of first edge pixels of edge that do not have edge correspondence with the respective second edge pixels in a corresponding second pixel block of the second plurality of pixel blocks, wherein two edge pixels have edge correspondence when the two edge pixels have a same edge location. frame and are associated with the same edge orientation and means for determining whether the first pixel block is a static block by comparing the number to a threshold.

[0133] Example 41 includes the subject matter of example 36, wherein the first frame has multiple video components, the first plurality of pixel blocks is associated with a video component foreground, the map is a first map and includes , further, means for segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a video component background different from the video component foreground. Example 41 also includes means for processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the second video component plane of the second preceding frame of the video sequence to create, based on the first criterion, a second map that identifies one or more static pixel blocks in the third plurality of pixel blocks. Example 41 further includes means for identifying, based on the first and second maps, the static region in the first frame of the video sequence.

[0134] Example 42 includes the subject matter of example 41, wherein the means for identifying, based on the first and second maps, the static region in the first frame of the video sequence includes means for combining the first map and the second map to determine a general map that identifies one or more static pixel blocks in the first frame of the video sequence.

[0135] Example 43 includes the subject matter of example 36, wherein the map is a first map, and further includes means for segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks, wherein those of the third plurality of pixel blocks partially overlap those of the first plurality of blocks. Example 43 also includes means for processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the previous second frame of the video sequence to create, based on the first criterion, a second map that identifies one or more blocks. pixel statics in the third plurality of pixel blocks, wherein those of the fourth plurality of pixel blocks partially overlap those of the second plurality of blocks. Example 43 further includes means for identifying, based on the first and second maps, the static region in the first frame of the video sequence.

[0136] Example 44 includes the subject matter of example 43, wherein the means for identifying, based on the first and second maps, the static region in the first frame of the video sequence includes means for combining the first map and the second map to determine a general map that identifies one or more static pixel subblocks in the first frame of the video sequence, wherein a first subblock in the first frame is included in a first block of the first plurality of pixel blocks and a first block of the third plurality of blocks, where the overall map has a better resolution than the first and second blocks. Example 44 also includes means for identifying the static region in the first frame of the video sequence based on the overview map.

[0137] Example 45 includes the subject matter of example 36, wherein the map is a first map and further includes means for adjusting the first criterion based on at least one of (1) a correlation determined between the first and the second frames of the video sequence or (2) evaluating a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence.

[0138] Example 46 is a system as defined in any one of claims 1 to 40, wherein the map is a first map and further includes means for adjusting the first criterion based on at least one of (36) a determined correlation between the first and second frames of the video sequence or (2) evaluation of a second prior map that identifies one or more static pixel blocks in the second plurality of pixel blocks corresponding to the second prior frame of the video sequence.

[0139] Example 47 is a system that includes means for carrying out a method as defined in any of examples 1 to 11.

[0140] Although certain exemplary methods, apparatus and articles of manufacture have been disclosed herein, the scope of coverage of this parent is not limited thereto. Rather, this patent covers all methods, apparatus and articles of manufacture that are reasonably within the scope of the claims of this patent.

Claims (10)

1. A video processing method comprising: segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks; segmenting pixels in a previous second frame of the video sequence into a second plurality of pixel blocks; compare (605) the pixels in each pixel block of the first video frame and a corresponding pixel block of the second video frame against a sum of absolute differences criterion to determine a first indication of whether a pixel block is a static block , where the pixel blocks of the first video frame and the corresponding pixel blocks of the second video frame are located at the same frame location and the sum of absolute differences is compared to a threshold; determining an edge map (610) that identifies edges in the first frame of the video sequence; counting a number of edge pixels (615) in each pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map; compare (615) the counted number of edge pixels for each pixel block in the first plurality of pixel blocks to a threshold to generate a second indication as to whether a pixel block is a static block for each pixel block in response to the number count of edge pixels is greater than or equal to the threshold; determine (620) a number of edge pixels in each pixel block of the first video frame not having edge correspondence with respective edge pixels in corresponding blocks of the second video frame, wherein two edge pixels have edge correspondence when the edge pixels have a similar frame location and are associated with the same edge orientation and comparing the number to a threshold to determine a third static block indication; determining a map that identifies one or more static pixel blocks in the first plurality of pixel blocks by combining (625) the results of the first, second and third indications; and identifying, based on the map, a static region in the first frame of the video sequence. 2. Method according to claim 1, characterized by the fact that the first frame presents multiple video components, the first plurality of pixel blocks is associated with a first video component, the map is a first map, and further comprises: segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a second video component plane different from the first component video plane; process the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the video component background of the previous second frame of the video sequence to create a second map identifying one or more static pixel blocks in the third plurality of blocks of pixels; and identifying, based on the first and second maps, the static region in the first frame of the video sequence. 3. Method according to claim 2, characterized by the fact that identifying, based on the first and second maps, the static region in the first frame of the video sequence comprises combining the first map and the second map to determine a map general that identifies one or more blocks of static pixels in the first frame of the video sequence. 4. Method according to claim 1, characterized by the fact that the map is a first map, and further comprises: segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks, those of the third plurality of blocks of pixels partially overlapping those of the first plurality of blocks; process the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the previous second frame of the video sequence to create a second map that identifies one or more static pixel blocks in the third plurality of pixel blocks, those of the fourth plurality of blocks of pixels partially overlapping those of the second plurality of blocks; and identifying, based on the first and second maps, the static region in the first frame of the video sequence. 5. Method according to claim 4, characterized by the fact that identifying, based on the first and second maps, the static region in the first frame of the video sequence comprises: combining the first map and the second map to determine a general map that identifies one or more sub-blocks of static pixels in the first frame of the video sequence, a first sub-block in the first frame being included in a first of the first plurality of pixel blocks and a first of the third plurality of blocks , the overall map having better resolution than the first and second blocks; and identify the static region in the first frame of the video sequence based on the overall map. 6. The method of claim 1, wherein the map is a first map, and further comprises adjusting the threshold for comparing (615) the counted number of edge pixels for each block of pixels in the first plurality. of blocks of pixels based on at least one of: i) a correlation determined between the first and second frames of the video sequence, or ii) evaluation of a second prior map identifying one or more blocks of static pixels in the second plurality of blocks of pixels corresponding to the previous second frame of the video sequence. 7. Machine-readable tangible storage media, at least one, characterized by comprising machine-readable instructions that, when executed, cause a machine to execute the method as defined in claim 1. 8. Apparatus characterized by comprising a processor configured to execute the method as defined in claim 1. 9. Video processing system characterized by comprising: means for segmenting pixels in a first frame of a video sequence into a first plurality of pixel blocks; means for segmenting pixels in a second preceding frame of the video sequence into a second plurality of pixel blocks; means for comparing pixels in each pixel block of the first video frame and a corresponding pixel block of the second video frame against a sum of absolute differences criterion to determine a first indication of whether a pixel block is a static block, wherein the pixel blocks of the first video frame and corresponding pixel blocks of the second video frame are located at the same frame location and the sum of absolute differences is compared to a threshold; means for determining an edge map that identifies edges in the first frame of the video sequence; means for counting a number of edge pixels in each pixel block of the first plurality of pixel blocks associated with the edges identified in the edge map; means for comparing the counted number of edge pixels for each pixel block in the first plurality of pixel blocks to a threshold for generating a second indication as to whether a pixel block is a static block for each pixel block in response to the counted number of edge pixels be greater than or equal to the threshold; means for determining a number of edge pixels in each pixel block of the first video frame having no edge correspondence with respective edge pixels in corresponding blocks of the second video frame, wherein two edge pixels have edge correspondence when the edge pixels have a similar frame location and are associated with the same edge orientation and comparing the number to a threshold to determine a third static block indication; means for determining a map that identifies one or more static pixel blocks in the first plurality of pixel blocks by combining the results of the first, second and third indications; and means for identifying, based on the map, a static region in the first frame of the video sequence. 10. Video processing system according to claim 9, characterized by the fact that the first frame presents multiple video components, the first plurality of pixel blocks is associated with a first video component plane, the map is a first map, and further comprises: means for segmenting the pixels in the first frame of the video sequence into a third plurality of pixel blocks associated with a second video component plane different from the first component video plane; means for processing the third plurality of pixel blocks and a fourth plurality of pixel blocks corresponding to the video component background of the previous second frame of the video sequence to create a second map identifying one or more static pixel blocks in the third plurality of pixel blocks; and means for identifying, based on the first and second maps, the static region in the first frame of the video sequence.