WO2007094329A1

WO2007094329A1 - Moving image processing device, moving image processing method, and moving image program

Info

Publication number: WO2007094329A1
Application number: PCT/JP2007/052547
Authority: WO
Inventors: Toru Yamada
Original assignee: Nec Corporation
Priority date: 2006-02-15
Filing date: 2007-02-07
Publication date: 2007-08-23
Also published as: JP5534261B2; JP2013017221A; JPWO2007094329A1; JP5516842B2

Abstract

An unsharpness strength determining unit (301) determines for each video frame if a high-frequency signal is to be removed or not. If the unsharpness strength determining unit (301) determines the high-frequency signal to be removed, it determines the high-frequency signal to be removed from the video frame. According to the determination of the unsharpness strength determining unit (301), an image unsharpening unit (302) subjects the moving image to unsharpening to remove the high-frequency signal from the video frame to unsharpen the image. The unsharpness strength determining unit (301) periodically varies the high-frequency signal to be removed from the video frame. An image encoding unit (303) encodes the video frame from which the high-frequency signal is removed.

Description

A moving picture processing apparatus, a moving picture processing method, and a moving picture processing program

The present invention relates to a moving image processing apparatus that encodes and outputs an input moving image, a moving image processing method, and a moving image processing program, and in particular, a moving image processing apparatus that removes a high-frequency signal from a video frame constituting a moving image, The present invention relates to a moving image processing method and a moving image processing program.

Background technology:

In order to realize long-time recording on DVD (registered trademark) and video distribution in a narrow communication network band, it is necessary to realize encoding at a low bit rate. However, there is a problem that encoding at a low bit rate is accompanied by degradation of image quality. As a method for solving this problem, there is a method of performing coding after removing in advance a high-frequency signal that is difficult to detect by human vision included in an image.

If the high frequency signal is removed from the moving image, the amount of code for encoding the high frequency signal is not necessary. Therefore, a moving image from which a high-frequency signal has been removed can be encoded at a low bit rate. However, when high-frequency signals are removed, the reproducibility of edges (shape contours) in the image is lost, and the image is blurred (meaning that the shape contour is not clear). In particular, if the rate of removing high-frequency signals is large, there is a problem that image quality degradation due to blur is detected by the viewer.

In addition, in the widely used moving picture coding scheme such as the MPEG (MoVinPgTureExrtsGroup) standard, the quantization coarseness is changed for each video frame.

For example, a B picture that performs predictive coding from both past and future video frames is generally quantized more coarsely than other video frames because that video frame does not become a predicted reference image of a subsequent video frame. It is. When video frames are roughly quantized, high-frequency signals tend to be removed by the quantization process. However, at the same time, the low-frequency signal is also roughly quantized, which increases the quantization distortion.

When the quantization distortion is large, for example, a difference in pixel value for each pixel block which is a unit for performing quantization becomes large between adjacent pixel blocks. This difference becomes a block distortion, which is easily detected by viewers as image quality degradation.

The following prior art document 1 describes an apparatus for solving this problem. The device described in the prior art document 1 determines the amount of blurring of the image in accordance with the magnitude of movement in the video. This device uses the human visual characteristic that high-frequency signals are difficult to detect in images with large movements, and blurs images with large movements weakly and images with small movements weakly. Such a function makes it difficult to detect blurred images.

The following prior art document 2 describes an apparatus that performs filtering processing for each video frame at regular intervals.

• Prior art document 1: Japanese Laid-Open Patent Publication No. 2 2003-3 3 3 3 0 (paragraphs 0 0 2 1 to 0 0 40, FIG. 1)

'Prior Art Document 2: Japanese Patent Application Laid-Open No. 2-2888788 (Page 3-7, Fig. 1) Disclosure of Invention:', Problem to be Solved by Invention:

However, the apparatus described in the above-mentioned prior art document 1 has a problem that blur is easily detected when the motion of the image is large and the blur is too strong. In addition, high-frequency signals cannot be removed sufficiently because images with small motion are weakened in blurring. For this reason, it is impossible to greatly reduce the amount of generated codes during encoding.

In addition, the apparatus described in the prior art document 2 performs a filtering process on each video frame at regular intervals. The filtering process performed on the video frame is preferably performed by changing the intensity step by step.

The present invention has been proposed in view of the above-described problems. That is, the present invention It is an object of the present invention to provide a moving image processing apparatus, a moving image processing method, and a moving image processing program that can sufficiently remove a high-frequency signal from a video frame.

Means to solve the problem:

The moving image processing apparatus according to the first aspect of the present invention determines the intensity at which the video frame is blurred (including determining not to blur). According to the determination by the blur intensity determining means and the blur intensity determining means, Image blurring means for blurring the image by removing high-frequency signals from the frame, and the blur intensity determining means changes the intensity of blurring when a predetermined number (one or more) of video frames continue. The blur intensity determining means changes the intensity of blurring periodically. Also, the blur intensity determining means changes the intensity to blur every other frame.

The blur strength determining means determines the strength to blur according to the change in pixel value between video frames.

The moving image processing apparatus according to the first aspect of the present invention further includes an image encoding unit that encodes the video frame output by the image blurring unit, and the blur strength determining unit includes the image encoding unit. The blur strength is determined according to the encoding method used when encoding the video frame.

The moving image processing apparatus according to the first aspect of the present invention further includes image encoding means for encoding the video frame output by the image blurring means, and the blur intensity determining means includes the K image encoding means as the video frame. The intensity to be blurred is determined according to the encoding method used when encoding and the pixel value change between video frames.

The moving image processing apparatus according to the first aspect of the present invention further includes local decoding means for generating a prediction reference frame by decoding the video frame encoded by the image encoding means, and storing the prediction reference frame A prediction reference frame blurring unit that removes the high-frequency signal of the prediction reference frame, and a prediction reference frame from which the prediction reference frame blurring unit has removed the high-frequency signal. The predicted reference frame blurring unit removes the high-frequency signal determined to be removed from the video frame by the blur strength determining unit from the predicted reference frame, and the image encoding unit includes the image blurring unit. Output video frame and predicted image The result of the subtraction process with the predicted image generated by the image generation means is encoded.

The moving image processing apparatus according to the first aspect of the present invention further includes decoding means for decoding the video frame encoded by the image encoding means, and second storage means for storing the video frame decoded by the decoding means. A second predicted image generating means for generating a motion compensated prediction predicted image from the video frame stored in the second storage means, a video frame decoded by the decoding means, and a second predicted image. Adding means for adding and outputting the predicted image generated by the generating means;

The moving image processing apparatus according to the first aspect of the present invention further includes a decoding means for decoding the video frame encoded by the image encoding means, and a second storage means for storing the video frame decoded by the decoding means. A second prediction reference frame blurring unit for removing a high-frequency signal determined to be removed by the blur intensity determination unit from the video frame stored in the second storage unit; and a second prediction reference frame blurring unit From the video frame from which the high-frequency signal has been removed, a second predicted image generating means for generating a predicted image for motion compensated prediction, a video frame decoded by the decoding means, and a prediction generated by the second predicted image generating means Adding means for adding and outputting the image;

The moving image processing apparatus according to the second aspect of the present invention is a moving image processing apparatus that processes a moving image composed of continuous video frames, and determines whether or not to perform fill-up processing for each video frame. When it is determined that the filter processing is to be performed, the in-loop filter evening determining means for determining the in-loop fill evening characteristic to be filtered, and the filter having the characteristics determined by the in-loop filter determining means for the input video frame. The input image filter processing means for performing the filtering process, the image encoding means for encoding the filtered video frame, and the local decoding for generating the prediction reference frame obtained by decoding the video frame encoded by the image encoding means Means, a first storage means for storing the prediction reference frame, and a prediction of the characteristics determined by the in-loop filter determination means. An in-loop filter processing means for performing a fill-in process on a frame, and a predicted image generation means for generating a predicted image from a prediction reference frame that the fill-in-loop process has performed in the loop. And the fill-in-loop processing means in the loop perform the fill-up process with a fill-in process with similar characteristics, and the image encoding means The result of subtracting the video frame output from the input image filter processing means and the predicted image generated by the predicted image generating means is encoded.

The moving image processing apparatus according to the second aspect of the present invention further includes a decoding unit that decodes the encoded video frame, a second storage unit that stores the video frame decoded by the decoding unit, and a second storage unit. A second in-loop filter processing means for performing a filtering process on the video frame stored in the storage means by the fill event having the characteristics determined by the in-loop fill setting determination means, and a second in-loop fill processing means. The second predicted image generating means for generating a predicted image of motion compensated prediction from the video frame subjected to the filtering process, the video frame decoded by the decoding means, and the prediction generated by the second predicted image generating means And adding means for adding and outputting the image.

The moving image processing method according to the third aspect of the present invention is a moving image processing method for processing a moving image composed of continuous video frames, and determines the intensity at which the video frame is blurred (determines that it is not blurred). Including a blur intensity determining step, and an image blur step for blurring the image by removing a high-frequency signal of the video frame according to the determination in the blur strength determining step. In the blur intensity determining step, a predetermined number of video frames ( Numbers greater than 1) It is characterized by changing the intensity of blurring when continuous.

The blur intensity determining step periodically changes the intensity of blurring. Further, the blur intensity determining step changes the intensity to be blurred every other frame.

The blur intensity determining step determines an intensity to be blurred according to a change in pixel value between video frames. .

The moving image processing method according to the third aspect of the present invention further includes an image encoding step for encoding the video frame output in the image blurring step, and the video frame in the image encoding step is a blur intensity determination step. The intensity to be blurred is determined according to the encoding method when encoding.

The moving image processing method according to the third aspect of the present invention further includes an image encoding step for encoding the video frame output in the image blurring step, and the video frame in the image encoding step is a blurring intensity determination step. Code when encoding The intensity to be blurred is determined according to the conversion method and the pixel value change between the video frames.

The moving image processing method according to the third aspect of the present invention further includes a local decoding step of generating a predicted reference frame by decoding a video frame encoded in an image encoding step, and removing a high-frequency signal of the predicted reference frame A prediction reference frame blurring step, and a prediction image generation step for generating a prediction image of motion compensated prediction from the prediction reference frame from which a high-frequency signal has been removed in the prediction reference frame blurring step, and in the prediction reference frame blurring step, The high-frequency signal determined to be removed from the video frame in the decision step is removed from the prediction reference frame, and in the image encoding step, the subtraction process between the video frame output in the image blurring step and the prediction image generated in the prediction image generation step The result of is encoded.

The moving image processing method according to the third aspect of the present invention further includes a decoding step for decoding the video frame encoded in the image encoding step, and a motion compensated prediction image from the video frame decoded in the decoding step. A second prediction image generation step to be generated; an addition step of adding and outputting the video frame decoded in the decoding step and the prediction image generated in the second prediction image generation step.

The moving image processing method according to the third aspect of the present invention further includes: a decoding step for decoding the video frame encoded in the image encoding step; and a blur intensity determination step for removing the video frame decoded in the decoding step. A second prediction reference frame blur step that removes the determined high-frequency signal, and a second prediction that generates a motion compensated prediction prediction image from the video frame from which the high-frequency signal was removed in the second prediction reference frame blur step. An image generation step; an addition step of adding and outputting the video frame decoded in the decoding step and the predicted image generated in the second predicted image generation step.

A moving image processing method according to a fourth aspect of the present invention is a moving image processing method for processing a moving image composed of continuous video frames, and determines whether or not to perform filtering for each video frame, When it is determined that the filter processing is to be performed, the in-loop fill event determining step for determining the in-loop fill event characteristic for performing the filter processing, and the fill factor of the characteristic determined in the in-loop filter determining step are applied to the input video frame. The input image filter processing step for performing the filter processing in the image, the image encoding step for encoding the filtered video frame, and the local reference frame for decoding the video frame encoded in the image encoding step. In-loop filter processing step that filters the prediction reference frame with the filter having the characteristics determined in the decoding step, and the in-loop fill filter determination step, and the prediction in which the in-loop fill filter processing step performs the filter processing A prediction image generation step for generating a prediction image from a reference frame. In the input image fill processing step and in-loop fill processing step, filtering is performed with a filter having similar characteristics. Video frame output in the input image filter processing step and predicted image It is characterized in that the result of the subtraction process with the predicted image generated in the generation step is encoded.

The moving image processing method according to the fourth aspect of the present invention further includes: a decoding step for decoding the encoded video frame; and a filter having the characteristics determined in the in-loop filter determination step on the video frame decoded in the decoding step. The second predicted image generation for generating a motion compensated prediction predicted image from the second in-loop filter processing step that performs the fill-in process and the video frame subjected to the filter processing in the second in-loop filter processing step. And an addition step for adding and outputting the video frame decoded in the decoding step and the predicted image generated in the second predicted image generating step.

A moving image processing program according to a fifth aspect of the present invention is a moving image processing program that causes a computer to process a moving image composed of continuous video frames, and determines the intensity of blurring the video frames in a computer evening. Yes (including determining not to blur) According to the determination in the blur intensity determination process and the blur intensity determination process, the image blur process is performed to blur the image by removing the high-frequency signal of the video frame. The processing is characterized by changing the intensity of blurring when a predetermined number (one or more) of video frames continues.

The moving image processing program according to the fifth aspect of the present invention causes the computer to change the intensity to be periodically blurred by the blur intensity determination process. Also, computer In the scare strength determination process, the strength to blur every other frame is changed.

The moving image processing program according to the fifth aspect of the present invention causes the computer to determine the intensity to be blurred according to the pixel value change between the video frames in the blur intensity determination process. A moving image processing program according to a fifth aspect of the present invention causes a computer to execute an image encoding process for encoding a video frame output in an image blur process, and in the blur intensity determination process, an image code The intensity to be blurred is determined according to the encoding method used when encoding video frames in the encoding process.

A moving image processing program according to a fifth aspect of the present invention causes a computer to execute an image encoding process for encoding a video frame output in an image blur process, and in the blur intensity determination process, an image code The intensity to be blurred is determined according to the encoding method used when encoding the video frame in the encoding process and the pixel value change between the video frames.

The moving image processing program according to the fifth aspect of the present invention includes a local decoding process for generating a predicted reference frame by decoding a video frame encoded by the image encoding process, and a high frequency of the predicted reference frame. Prediction reference frame blurring is performed by performing a prediction reference frame blurring process that removes a signal and a prediction image generation process that generates a predicted image of motion compensated prediction from a prediction reference frame from which a high-frequency signal has been removed by the prediction reference frame blurring process. In the process, the high-frequency signal determined to be removed from the video frame by the blur intensity determination process is removed from the prediction reference frame, and the video frame output by the image blur process and the predicted image generation process are generated in the image encoding process. The result of the subtraction process with the predicted image is encoded.

The moving image processing program according to the fifth aspect of the present invention is a computer that further includes a decoding process for decoding a video frame encoded by the image encoding process, and a motion compensation prediction from the video frame decoded by the decoding process. A second predicted image generation process for generating a predicted image, an addition process for adding and outputting the video frame decoded by the decoding process and the predicted image generated by the second predicted image generation process are executed.

The moving image processing program according to the fifth aspect of the present invention is a computer that performs decoding processing for decoding a video frame encoded by the image encoding processing, and blur intensity determination processing from the video frame decoded by the decoding processing. Removes high-frequency signals that are determined to be removed The second predicted reference frame blurring process, the second predicted reference frame blurring process, the second predicted reference frame blurring process, the second predicted image generation process for generating a motion compensated predicted image from the video frame from which the high-frequency signal has been removed, and the decoding process. You may perform the addition process which adds and outputs the decoded video frame and the prediction image produced | generated by the 2nd prediction image production | generation process.

A moving image processing program according to a sixth aspect of the present invention is a moving image processing program for causing a computer to process a moving image composed of continuous video frames, and for each video frame in a computer, a filter process is performed. If it is determined whether or not to perform the filter processing, the in-loop filter determination processing for determining the filter characteristics in the loop to perform the filter processing and the in-loop filter on the input video frame An input image filtering execution process for performing a filter process with a filter having the characteristics determined in the determination process, an image encoding process for encoding the filtered video frame, and a decoding of the video frame encoded by the image encoding process Prediction using a local decoding process that generates the predicted reference frame and a filter with the characteristics determined by the in-loop filter determination process. Input image filtering is performed by executing in-loop filtering that performs filtering on the reference frame and predicted image generation that generates a predicted image from the predicted reference frame that has been filtered in the in-loop filtering. In the process and filtering in the loop, the filter process is executed with the filter of the same characteristics, and the image frame is generated by the image encoding process and the video frame output by the input image filter execution process. The result of the subtraction process with the predicted image is encoded.

The moving image processing program according to the sixth aspect of the present invention is a computer that further performs decoding processing for decoding an encoded video frame, and processing for decoding a video frame decoded by the decoding processing by an in-loop fill event determination processing. Generates a predicted image for motion compensated prediction from the second in-loop filtering execution process that performs filtering with the determined characteristic fill event and the second in-loop fill event execution process. The second predicted image generation process, the video frame decoded by the decoding process, and the addition process for adding and outputting the predicted image generated by the second predicted image generation process Let

The invention's effect:

The first effect of the present invention is to control the intensity of blurring for each video frame, so that it is not easy for the viewer to detect whether the blurring process has been performed or not. It can be removed.

In particular, if the video frame that has been subjected to the blurring process and the video frame that has not been subjected to the blurring process are configured to be periodic, whether the viewer has been subjected to the blurring process. It is possible to remove high-frequency signals from moving images without more easily detecting whether or not.

The second effect of the present invention is that it is difficult to detect that the blurring process has been performed, and the subjective image quality can be improved when a moving image is encoded.

The reason for this is that first, a moving image is composed of video frames that have been subjected to the blurring process and video frames that have not been subjected to the blurring process, making it difficult to detect blur power during playback. Second, since the high-frequency signal is removed in the video frame that has been subjected to the blurring process, the amount of generated code can be reduced, and quantization can be performed in a small quantization step, thereby reducing the quantization error. It is.

If the device is configured to determine the high-frequency signal to be removed from the video frame according to the pixel value change between the video frames and the encoding method when encoding the video frame, Taking advantage of human visual characteristics, it is possible to make it difficult for viewers to detect that blurring has been applied.

When the apparatus removes the high-frequency signal from the prediction reference frame obtained by decoding the encoded video frame, the apparatus is configured to remove the high-frequency signal and generate a prediction image in the same manner as the blurring process at the time of encoding. If so, video frames that have been blurred can be decoded correctly.

When the device is configured to generate a motion compensated prediction image from a video frame obtained by decoding a video frame that has been encoded with high-frequency signals removed, an encoding scheme such as MPEG-2 With the same configuration as a video decoding device that decodes video data encoded with the wear.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram showing a first embodiment of a moving image processing apparatus.

FIG. 2 is an explanatory diagram showing the configuration of a video in which video frames that are blurred and video frames that are not blurred are alternated.

FIG. 3 is a block diagram showing a second embodiment of the moving image processing apparatus.

FIG. 4 is a flowchart schematically showing the operation of the moving image processing apparatus of the second embodiment.

FIG. 5 is a block diagram illustrating a configuration example of a decoding device.

FIG. 6 is a flowchart schematically showing the operation of the decoding apparatus.

FIG. 7 is a block diagram showing the configuration of the decoding apparatus in the third embodiment.

FIG. 8 is a block diagram showing a fourth embodiment of the moving image processing apparatus.

FIG. 9 is a flowchart showing schematically the operation of the moving image processing apparatus of the fourth embodiment.

FIG. 10 is a block diagram showing the configuration of the decoding apparatus in the fourth embodiment. FIG. 11 is a flowchart schematically showing the operation of the decoding apparatus in the fourth embodiment.

FIG. 12 is a block diagram showing a configuration !! when the moving image processing apparatus is realized by a computer system.

Best Mode for Carrying Out the Invention:

A first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a first embodiment of a moving image processing apparatus according to the present invention.

The moving image processing apparatus shown in FIG. 1 includes a blur intensity determining apparatus 20 1 that determines the intensity at which a video frame is blurred, and an image blur apparatus 2 0 2 that performs processing to remove a high-frequency signal from the video frame and blur the image. including.

The blur intensity determination device 2 0 1 determines whether or not to perform the process of blurring each video frame when the input image is input, and the blur intensity when performing the process of blurring the video frame. In this example and the following examples, the blur strength is This corresponds to the frequency of the high-frequency signal removed from the image frame.

The intensity of blur is not constant between successive video frames. For example, the blur intensity determination device 2 '0 1 determines the blur intensity so that a video frame subjected to blur processing and a video frame not subjected to blur processing are alternated, and a video frame that strongly blurs and a video frame that blurs weakly. The blur intensity is determined so that and alternate. In other words, the blur intensity determining apparatus 210 periodically changes the intensity of the blurring process performed on the video frame. Further, the period for changing the intensity to be blurred by the blur intensity determining apparatus 2 0 1 may or may not be constant. In other words, the intensity to blur aperiodically may be changed.

As shown in FIG. 2, the blur intensity determination device 20 1 does not have to change the intensity to be blurred for each video frame. For example, the blur intensity determining device 2 0 1 may change the intensity to be blurred every two video frames.

The blur intensity determination device 2 0 1 determines the blur intensity in consideration of the characteristics of the video frame itself such as the amount of change in luminance value. Specifically, the blur intensity determining device 2 0 1 has, for example, an average moving amount (motion vector amount) of 16 pixels, and a luminance value change amount that takes into account the moving amount is 2 per pixel. If so, decide to blur. Further, the blur intensity determination device 20 1 may determine the intensity to be blurred in consideration of the encoding method when the input image is encoded. For example, the blur intensity determination device 210 may change the intensity of blurring between a video frame that employs interframe prediction and a video frame that does not. '

The blur intensity determining device 2 0 1 determines the intensity for blurring each video frame, for example, in one of the 10 stages.

The blur intensity determining apparatus 201 determines whether or not to perform the blur process on each video frame, and when determining to perform the blur process, determines the blur strength in the video frame blur process. In this case, the image blur device 2 0 2 removes the high-frequency signal of the video frame determined to be blurred according to the strength to be blurred. Output. The image blurring device 202 outputs the video frame determined not to be subjected to the blur process without performing the blur process. For example, a low-pass filter is used to remove high-frequency signals.

Specifically, the blur intensity determining device 2 0 1, for example, when blurring a video frame strongly, for example, a high frequency signal (for example, about 50% or more of the maximum frequency (for example, 4.2 MHz)) (for example, 2. Signals above 1 MHz are removed.

Further, the blur intensity determining device 20 0 1, for example, when blurring a video frame weakly, for example, a high-frequency signal (for example, 3 .0) having a frequency of about 90% of the maximum frequency (for example, 4.2 MHz). 8) Signals above 8 MHz are removed.

In this specification, removing a high-frequency signal from a video frame is referred to as blurring processing.

As described above, according to the present embodiment, the intensity of blurring is controlled for each video frame, and video frames that are subjected to the blurring process and video frames that are not subjected to the blurring process are configured alternately. Therefore, it is possible to remove the high-frequency signal of the moving image (video frame) without easily detecting whether or not the blurring process is performed on the viewer.

Therefore, it is possible to realize encoding at a low bit rate by reducing the amount of code for encoding a video frame while preventing the viewer from detecting blur. ., Also, if the high-frequency signal is not removed at all, that is, if no blurring process is performed, the amount of generated code increases. In that case, it is necessary to increase the quantization step in order to encode at a low bit rate. As a result, quantization error occurs and the image quality deteriorates.

However, in this embodiment, since the high-frequency signal is removed from the video frame subjected to the blurring process, the generated code amount is reduced as a whole. Therefore, even when encoding at a low bit rate, quantization can be performed with a small quantization step, and the quantum error can be reduced. For this reason, it is possible to make it difficult to detect a decrease in image quality due to a quantization error.

In other words, it is difficult to detect that the process of blurring the viewer has been performed, and a moving image (movie) In order to reduce the quantization error when encoding (image frames), the subjective image quality (image quality perceived by the viewer) is higher than when high-frequency signals are removed from all video frames or when no high-frequency signals are removed. Can be improved.

Next, a second embodiment of the present invention will be described with reference to the drawings. FIG. 3 is a block diagram showing a second embodiment of the moving image processing apparatus according to the present invention.

As shown in FIG. 3, the moving image processing apparatus according to the second embodiment includes a blur intensity determining device (blur intensity determining means) 3 0 1 for determining the blur intensity of a video frame, and a high-frequency signal of the video frame. Blurring device (image blurring means) 3 0 2 which removes image, image coding device (image coding means) 3 0 3 for encoding input image, and prediction reference frame of image to be encoded Local decoding device (local decoding means) 3 0 4, frame memory for storing (storing) prediction reference frames (first storage means) 3 0 5, and input for encoding prediction reference frames Prediction reference frame blurring device (prediction reference frame blurring means) 3 0 6 blurring at the same intensity as the image, and prediction image generation device (prediction image generation means) 3 0 7 for generating a motion compensated prediction image from the prediction reference frame Have .

In this embodiment, an apparatus that performs encoding using the MPEG encoding system is assumed as the moving image processing apparatus. However, the moving image processing apparatus according to the present invention is not limited to the one that performs encoding by the MPEG encoding method. , Blur intensity determination device 3 0 1 determines whether or not to blur each video frame when an input image is input, and blur intensity (video) when performing blur processing on the video frame. Determine the frequency of the signal to be removed from the frame.

The strength to blur is not constant. The blur intensity determination device 3 0 1 determines, for example, that video frames that are to be blurred and video frames that are not to be blurred are alternated, and video frames that are strongly blurred and video frames that are weakly blurred are alternated. To decide.

The blur intensity determination device 3 0 1 determines the intensity to be blurred based on the information output from the image encoding device 3 0 3. For example, the intensity to be blurred is determined based on the encoding method, and the intensity to be blurred is determined based on a change in pixel value between video frames of the image. The blur intensity determining device 3 0 1 determines the blur intensity based on the combination of the encoding method and the change in pixel value between video frames of the image. The blur intensity information indicating what kind of blur processing has been performed is output to the image encoding device 303 and the prediction reference frame blurring device 30.

The image blurring device 3 0 2 blurs the image frame determined to be blurred by the blur strength determination device 3 0 1 from the input image with the blur strength determined by the blur strength determination device 3 0 1 ( The image is subjected to a blurring process) and output to the image encoding device 303. For example, a low-pass filter is used to blur the image.

Also, the image blurring device 30 2 outputs to the image encoding device 303 without blurring the video frame determined not to be subjected to the blurring process by the blurring intensity determination device 3 0 1 among the input images.

The image encoding device 30 3 encodes and outputs the video frame output by the image blurring device 30 2. The image encoding device 303 also encodes the blur intensity information and encodes the encoded moving image data (video frame) so as to include the blur intensity information.

The local decoding device 30 4 decodes the video frame encoded by the image encoding device 30 3 for use as a prediction reference frame for motion compensation prediction of a video frame to be encoded later. The frame memory 30 5 stores the video frame decoded by the local decoding device 30 04.

The prediction reference frame blurring device 3 06 performs a process of blurring the video frame (prediction reference frame) stored in the frame memory 3 0 5. The prediction reference frame blurring device 300 performs blurring processing in the same manner as the method indicated by the blur strength information, based on the blur strength information output from the blur strength determination device 3101.

The predicted image generation device 3 07 generates a predicted image using the predicted reference frame that has been subjected to the blurring process.

The predicted image generated by the predicted image generation device 3 0 7 is subtracted from the video frame output by the image blurring device 3 0 2, and the subtraction result is input to the image encoding device 3 0 3. Further, the predicted image generated by the predicted image generation device 3 07 is added to the video frame decoded by the local decoding device 3 04 and stored in the frame memory 3 0 5. The subtraction process is performed by, for example, a subtracter, and the addition process is performed by, for example, an adder.

Next, the operation of the moving image processing apparatus of the second embodiment will be described with reference to the drawings. FIG. 4 is a flowchart schematically showing the operation of the moving image processing apparatus of the second embodiment. The process shown in FIG. 4 is a process in the process until a video frame encoded without using a prediction reference frame is output first, and then a video frame encoded using a prediction reference frame is output. It is.

The blur intensity determination device 3 0 1 determines whether or not to perform the process of blurring each video frame when an input image is input, and the blur intensity when performing the process of blurring the video frame (removed from the video). (Frequency of signal to be transmitted) is determined (steps S 1 0 1 and S 1 0 2)

The image blurring device 3 0 2 blurs the video frame determined by the blur intensity determining device 3 0 1 to be blurred in the input image with the blur intensity determined by the blur intensity determining device 3 0 1 (the blur process is performed). And output to the image encoding device 30 (step S 1 0 3).

The image encoding device 30 3 encodes the video frame output by the image blurring device 30 2 and outputs it as data relating to the first frame (step S 1 0 4). Since the video frame output by the image encoding device 3 0 3 is used as a prediction reference frame of a video frame to be encoded later, the local decoding device 3 0 4 is output by the image encoding device 3 0 3. The decoded video frame is decoded (step S 1 0 5). The predicted reference frame blurring device 30 6 performs processing (fill processing) to blur the video frame (predicted reference frame) stored in the frame memory 3 05 (step S 1 0 6).

The predicted image generation apparatus 30 07 generates a predicted image using the predicted reference frame that has been subjected to the blurring process (filter process) (step S 1 07). The predicted image generated by the predicted image generation device 6 0 7 is output from the image blurring device 3 0 2 by the subtractor. Subtracted from the video frame (step S 1 0 8).

The image encoding device 30 3 encodes the output of the subtracter and outputs it as data relating to the second frame (steps S 1 0 9 and S 1 1 0).

Next, decoding of the encoded moving image will be described. FIG. 5 is a block diagram illustrating a configuration example of a decoding device.

The decoding device shown in FIG. 5 stores (stores) an image decoding device (decoding means) 4 0 1 for decoding an encoded moving image and uses the decoded video frame as a prediction reference frame. Frame memory (second storage means) 4 0 2, prediction reference frame blurring device (second prediction reference frame blurring means) that performs processing to blur the prediction reference frame 4 0 3, and motion compensation from the prediction reference frame A predicted image generating device (second predicted image generating means) 40 4 for generating a predicted image of the prediction.

The moving image processing apparatus may include the function of the decoding apparatus illustrated in FIG. The image decoding device 4 0 1 decodes the encoded video frame. The image decoding device 4 0 1 also decodes the encoded blur intensity information at the same time. Then, the image decoding device 4001 outputs the decoded blur intensity information to the prediction reference frame blurring device 4003.

In order to use the video frame decoded by the image decoding device 4101 as a predicted reference frame, the frame memory 40.2 uses the video frame (frame predicted prediction) decoded by the image decoding device 4101. Remember.

The predictive reference frame blurring device 40 3 uses the prediction reference frame stored in the frame memory 4 0 2 based on the blur intensity information decoded by the image decoding device 4 0 1 at the time of encoding. Apply blurring treatment in the same way and with the same strength.

The predicted image generation device 40 4 generates a predicted image using the predicted reference frame subjected to the processing performed by the prediction reference frame blurring device 40 3. The predicted image generated by the predicted image generation device 40 4 is added to the video frame decoded by the image decoding device 40 1 and output. The addition process is performed by, for example, an adder (addition unit).

Next, the operation of the decoding device will be described with reference to the drawings. Figure 6 shows a decryption device It is a flowchart which shows typically operation | movement. The process shown in Fig. 6 is an example of a case where decoding is performed using a prediction reference frame.

The image decoding device 4 0 1 decodes the encoded video frame when the encoded video frame is input without using the prediction reference frame (Step S 2 0 Do).

The prediction reference frame blurring device 40 3 performs the same process and the same blur process (fill evening process) as those at the time of encoding on the prediction reference frame (step S 2 0 2). The predicted image generation device 40 4 generates a predicted image using the predicted reference frame subjected to the processing (filter processing) blurred by the predicted reference frame blurring device 40 3 (step S 2 0 3).

The predicted image generated by the predicted image generation device 4 04 is added by the adder to the video frame decoded by the image decoding device 7 0 1. Then, the addition result is output from the adder (steps S 2 0 4 and S 2 0 5) ₀

The operation of each device included in the moving image processing device may be performed by a CPU that executes processing according to program control. Specifically, the moving image processing apparatus is a moving image processing program that processes a moving image composed of continuous video frames in a combination evening, and determines the strength of blurring the video frames to the computer (not blurry). In accordance with the determination in the blur intensity determination process and the blur intensity determination process, an image blur process for blurring an image by removing a high-frequency signal from a video frame is executed. It is equipped with a video processing program that is characterized by changing the intensity of blurring when a certain number of video frames continue (a number greater than 1) in the intensity determination process. C PU may execute each of the above processes.

According to the present embodiment, based on the determination of the blur intensity determination device 3 0 1, whether or not to perform the blurring process for each video frame and the blurring intensity when performing the blurring process are changed, thereby changing the video frame. Can be encoded and decoded.

Therefore, similar to the first embodiment, it is possible to improve the subjective image quality by removing the high frequency signal of the moving image without easily detecting whether or not the blurring process is performed on the viewer. . Next, a third embodiment of the present invention will be described. The configuration of the moving image processing apparatus is the same as that of the moving image processing apparatus of the second embodiment shown in FIG. However, in the third embodiment, the decoding device is configured as shown in FIG. In other words, a device equivalent to the prediction reference frame blurring device 4 03 is not provided. .

Note that the moving image processing apparatus that performs the encoding process may include the function of the decoding apparatus illustrated in FIG.

The decoding apparatus shown in FIG. 7 includes an image decoding apparatus 5 0 1 that decodes encoded video data, and a frame memory 5 0 2 that stores (stores) the decoded video frame for use as a prediction reference frame. And a predicted image generation device 50 3 that generates a predicted image of motion compensated prediction from the predicted reference frame.

The decoding apparatus shown in FIG. 7 has a configuration obtained by removing the prediction reference frame blurring apparatus 40 3 from the decoding apparatus shown in FIG. The decoding device shown in FIG. 7 has the same configuration as that of a moving image decoding device that decodes moving image data encoded by an encoding method such as MPEGG-2.

The input image is encoded by the moving image processing apparatus shown in FIG. Therefore, the prediction reference frames used for motion compensation prediction are blurred at different strengths for each video frame.

On the other hand, the encoded video frame is decoded by the decoding device shown in FIG. The decoding apparatus shown in FIG. 7 does not include means for blurring the prediction reference frame. Therefore, since the decoding apparatus shown in FIG. 7 cannot generate a prediction reference frame that matches the prediction reference frame used at the time of encoding, the video frame encoded by the moving image processing apparatus shown in FIG. It cannot be decrypted correctly. '

Therefore, the decoded video frame is different from the video frame before being encoded by the moving image processing apparatus shown in FIG. The prediction residual by motion compensated prediction is composed of the difference between the prediction reference frame blurred at the time of encoding and the blurred input video frame. When decoding a video frame, this prediction residual is added to the prediction reference frame that is not blurred.

The input image is not blurred as in the case of encoding using the normal MPEG-2 method. The image data (video frame) when encoded into the image data (video frame) when decoded by the decoding device shown in FIG. 7 and the moving image processing device shown in FIG. When the encoded image data (video frame) is compared with the image data (video frame) when decoded by the decoding device shown in Fig. 7, the difference between the decoded image data (video frame) is Whether there is a high-frequency signal of the prediction residual.

For this reason, in this embodiment, when the moving image data encoded by the moving image processing apparatus shown in FIG. 3 is decoded by the decoding apparatus shown in FIG. 7, it is not possible to correctly decode the image data (video frame). However, because high-frequency signals are difficult to detect due to human visual characteristics, the difference (difference between image data (video frame) before encoding and image data (video frame) before decoding) is difficult for the viewer to detect. can do.

In addition, since the blurred video frame contains only a few high-frequency signals, encoding is simplified. Therefore, the generated code amount can be reduced. Since the reduced code amount can be assigned to the video frame that has not been subjected to the blurring process, the image quality of the video frame that has not been subjected to the blurring process can be improved. Therefore, according to the present embodiment, it is possible to improve the subjective image quality of the entire video.

Next, a fourth embodiment of the present invention will be described with reference to the drawings. The moving image processing apparatus according to the fourth embodiment of the present invention is an H. 261 system (I TU-T (Inte, rnationa 1 Teleco mm unicati on Un i on Te 1 eco mm unicati on St and ad izati). (Sector based on H. 261 recommendation)), the input image is filtered with the same filter characteristics as the in-loop filter, and the prediction residual is obtained. Reduce the difference and reduce the amount of generated code.

In this embodiment, a case where a video frame is encoded by the H. 261 method and a case where a video frame encoded by the H. 261 method is decoded will be described as examples. FIG. 8 is a block diagram showing a fourth embodiment of the moving image processing apparatus according to the present invention.

The moving image processing apparatus shown in FIG. 8 has an in-loop filter determining device (in-loop filter determining means) 601 that determines the type of in-loop filter, and an input image. An input image fill processing device (input image filter processing means) 6 0 2 'for performing fill evening processing using a fill evening equal to the in-loop fill evening provided in the encoding loop, and encoding the input image Image encoding device (image encoding means) 6 0 3, local decoding device (local decoding means) 6 0 4 for generating a prediction reference frame of an image to be encoded, and storing a prediction reference frame (memory) Frame memory (first storage means) 6 0 5, intra-loop filter processing device (in-loop filter processing means) 6 0 6 for removing high-frequency signals of prediction reference frames, and prediction of motion compensated prediction from prediction reference frames A predicted image generating device (predicted image generating means) 6 0 7 for generating an image. The in-loop filter determination device 6 0 1 determines whether or not to apply a process (filter process) to each image frame based on the image frame and the type of in-loop filter to be used. The in-loop fill event determining device 60 1 determines the type of in-loop file event in consideration of the amount of generated code by the output of the image encoding device 60 3 and the complexity of the image data.

Further, the in-loop fill event determining device 60 1 outputs filter information indicating the type of the in-loop fill event to be used to the image encoding device 63 and the in-loop filter processing device 6 06.

The input image fill processing device 6 0 2 selects a video frame determined to be blurred by the in-loop filter determination device 6 0 1 out of the video frames, in the loop determined by the in-loop filter determination device 6 0 1. The image is blurred (filled with blur processing (fill evening processing)) and output to the image encoding device 63.

Also, the input image filter processing device 60 2 does not perform the processing (filter processing) of the input image that is determined not to be subjected to the processing to be blurred by the in-loop filter determination device 6 0 1. The image is output to the image encoding device 6 0 3.

The image encoding device 63 encodes and outputs the video frame output from the input image filter processing device 60 2 and the filter information output from the in-loop filter determination device 6 01.

The local decoding device 6 0 4 is encoded by the image encoding device 6 0 3 for use as a prediction reference frame for motion compensation prediction of a video frame to be encoded later. Decode the video frame. The frame memory 60 5 stores the video frame decoded by the local decoding device 60 4. 'The in-loop filter device 6 0 6. performs processing to blur the video frame (predicted reference frame) stored in the frame memory 6 0 5. Note that the in-loop filter device 60 6 uses the same filter as the input image filter processing device 60 2 based on the filter information output from the in-loop filter determination device 6 0 1 to blur the predicted reference frame. Apply (filter processing).

The predicted image generation device 60 generates a predicted image using the predicted reference frame that has been subjected to the blurring process (fill evening process). The predicted image generated by the predicted image generation device 6 07 is subtracted from the video frame output from the input image filter processing device 60 2. Further, the predicted image generated by the predicted image generation device 6 07 is added to the video frame decoded by the local decoding device 6 04 and stored in the frame memory 6 05. For example, a low-pass filter is used for filtering.

Next, the operation of the moving image processing apparatus of the fourth embodiment will be described with reference to the drawings. FIG. 9 is a flowchart schematically showing the operation of the moving image processing apparatus of the fourth embodiment.

The in-loop filter determination device 6 0 1 determines whether or not to apply a blurring process (filter process) to each video frame when an image data (video frame) is input, and the type of in-loop filter to be used. Determine (Steps S 3 0 1, S 3 0 2). The input image filter processing device 60 2 selects a video frame that is determined to be blurred by the in-loop filter setting device 6 0 1 from the video frames. Blur in Phil evening. In other words, blur processing (filter processing) is performed. Then, the input image filter processing device 60 2 outputs the video frame subjected to the blurring process to the image coding device 60 3 (step S 3 0 3).

The image encoding device 6 03 encodes the video frame output by the input image filter processing device 6 02 and outputs it as data relating to the first frame (step S 3 0 4). Since the video frame output from the image encoding device 6 03 is used as a prediction reference frame of a video frame to be encoded later, the local decoding device 6 0 4 outputs the video frame output from the image encoding device 6 0 3. The video frame is decoded (step S 3 0 5). The in-loop fill device 6 06 applies a process (filter process) to blur the video frame (predictive reference frame) stored in the frame memory 6 05 (step S 3 06). The predicted image generation device 6 07 generates a predicted image using the predicted reference frame that has been subjected to the blurring process (filter process) (step S 3 07). The predicted image generated by the predicted image generation device 6 07 is subtracted from the video frame output from the input image filter processing device 60 2 by a subtracter (step S 3 0 8).

The image encoding device 60 3 encodes the output of the subtracter and outputs the encoded image frame (steps S 3 09 and S 3 1 0).

Next, decoding of the encoded moving image will be described. In the fourth embodiment, decoding is performed by the decoding device shown in FIG.

The decoding apparatus shown in FIG. 10 stores an image decoding apparatus (decoding means) 7 0 1 for decoding an encoded moving image and a decoded video frame for use as a prediction reference frame (memory). A frame memory (second storage means) 7 0 2, an in-loop filter processing device (second in-loop filter processing means) 7 0 3 for removing high-frequency signals from the prediction reference frame, and a prediction reference frame And a predicted image generation device (second predicted image generation means) 7 0 4 for generating a predicted image of motion compensation prediction.

Note that the moving image processing apparatus may include the function of the decoding apparatus illustrated in FIG.

The image decoding device 7 0 1 decodes the encoded video frame and filter information. The image decoding device 70 1 outputs the decoded fill information to the in-loop filter processing device 70 3. The frame memory 70 2 stores the video frame decoded by the image decoding device 70 1 for use as a prediction reference frame. The in-loop filter device 70 3 performs a blurring process (filter processing) on the prediction reference frame stored in the frame memory 70 2 based on the filter information output from the image decoding device 70 1. . The predicted image generation device 70 4 generates a predicted image using the predicted reference frame subjected to the fill-up process. The predicted image generated by the predicted image generation device 70 4 is added to the video frame decoded by the image decoding device 70 1 and output.

Next, the operation of the decoding device will be described with reference to the drawings. FIG. 11 is a flowchart schematically showing the operation of the decoding apparatus according to the fourth embodiment.

The image decoding device 7 0 1 decodes the encoded video frame (step S 4 0 1).

The in-loop filter device 70 3 performs the same process and the process of blurring with the same intensity (fill process) on the prediction reference frame (step S 4 0 2). The predicted image generation device 70 4 generates a predicted image using the predicted reference frame that has been subjected to the processing (filter processing) blurred by the in-loop filter device 70 3 (step S 4 0 3). The predicted image generated by the predicted image generation device 70 4 is added to the video frame decoded by the image decoding device 7 0 1 by an adder, and the addition result is output from the adder (step S 4 0 4 , S 4 0 5).

The operation of each device included in the moving image processing device may be performed by a CPU that executes processing according to program control. Specifically, when the moving image processing apparatus decides whether or not to perform the filtering process for each video frame in the combination evening, and decides to perform the filtering process, the in-loop filter characteristic for performing the filtering process is determined. In-loop filter determination processing, and input image filtering execution processing for performing fill-up processing on the input video frame in accordance with the characteristics of the filter determined in the loop-in-loop filtering processing, and fill-up processing. The image encoding process that encodes the video frame, the local decoding process that generates the prediction reference frame obtained by decoding the video frame encoded by the image encoding process, and the filter having the characteristics determined by the in-loop filter determination process. The filter processing is performed by the intra-loop filtering execution processing that filters the prediction reference frame and the intra-loop filtering execution processing. A predicted image generation process for generating a predicted image from the predicted reference frame that has been processed, and a filter process with a filter having the same characteristics in the input image filtering execution process and the in-loop filtering execution process. In the image encoding process, the input image filtering execution process is output. PT / JP2007 / 052547

A moving picture processing program is installed, which encodes the result of the subtraction process between the input video frame and the predicted picture generated by the predicted picture generation process. The moving image processing program may be executed by CPU.

According to this embodiment, since the filter processing is performed on the input image using the filter having the same characteristics as the filter processing in the loop in which the filter processing is performed on the prediction reference frame, the high frequency signal is generated from the prediction reference frame and the input image. Are removed to the same extent, and the prediction residual can be reduced. Therefore, the amount of code required for encoding can be reduced.

In addition, since the decoding apparatus in the present embodiment has the same configuration as that of an encoding scheme such as the H. 26 1 scheme, only the portion that performs image coding is changed to realize the present embodiment. Can do.

FIG. 12 is a block diagram showing a configuration example when the moving image processing apparatus of the first embodiment is realized by a computer system.

In the configuration example shown in FIG. 12, the computer system has a processor 8 0 1. The processor 8 0 1 is connected to an input / output buffer 8 1 1 and an output data buffer 8 1 2 and a program memory 8 0 2 storing a necessary program. .

Program modules stored in the program memory 8 0 2 include a blur intensity determination process 8 1 3 and an image blur process 8 1 4 in addition to the main program and program. The main program is a main program that executes moving image processing. The blur intensity determination processing program 8 13 is a program for realizing the function of the blur intensity determination apparatus 2 0 1. The image blur processing program 8 1 4 is a program for realizing the function of the image blurring device 2 0 2. When the processor 80 1 executes the main program and each functional module, the moving image processing in the moving image processing apparatus of the first embodiment is executed.

The moving image processing apparatuses according to the second to fourth embodiments described above are also realized by mounting program modules for realizing the functions of the blocks in the computer system. Next, a more specific embodiment of the moving image processing apparatus according to the present invention will be described. Here, a video of SD TV (Standard Definition T e 1 evision) size (horizontal direction: 7 20 pixels, vertical direction: 4 80 pixels, 29.9 7 frames per second) As an example, the video is input to the moving image processing apparatus shown in FIG. 3 and is encoded by the MPEG encoding method.

The image encoding device 3 0 3 is a frame (I picture) that independently encodes one video frame, a frame (P picture) that predicts from a past video frame and encodes a prediction error, Also, it encodes to one of three types of pictures: a frame (B picture) that encodes the prediction error that does not predict from past and future video frames.

Here, only the video frames encoded as B pictures out of the input moving images are subjected to the blurring process by the image blurring device 300, and the video frames encoded as I and P pictures are blurred. As an example, the data is encoded as is without being applied. Whether or not to perform the blurring process is determined by the blur intensity determining apparatus 3 0 1.

Thus, the input image that has been subjected to different blurring processing depending on the type of picture is encoded by the image encoding device 303. In addition to encoding in the same way as the MPEG method using discrete cosign transformation, quantization, and variable-length coding, the image encoding device 30 3 also includes information on how the input image was blurred. Encode. The encoded video frame is decoded by the local decoding device 30 4 and stored in the frame memory 3 0 5 for use as a prediction reference frame. When the encoded video frame is a B picture, the prediction reference frame blurring device 3 06 performs a blurring process on the prediction reference frame stored in the frame memory 3 0 5. At this time, the prediction reference frame is blurred by a method similar to the method in which the image blurring device 3002 blurs the input image.

The predicted image generation device 30 generates a predicted image using the blurred predicted reference frame. Then, the difference between the input image and the predicted image is taken and the difference is encoded. Predictive reference frame blur if the encoded video frame is a P picture The device 30 06 does not perform the blurring process, the predicted image is generated by the predicted image generation device 30 07, the difference from the input image is taken, and the difference is encoded. 'When decoding the encoded moving image data, the video frame is restored by the image decoding device 4 0 1 shown in FIG. At that time, information on how the video frame was blurred at the time of encoding is also decoded. The decoded video frame is stored in the frame memory 402 for use as a prediction reference frame.

When the decoded frame is a B picture, the prediction reference frame stored in the frame memory 4 0 2 is blurred by the prediction reference frame blurring device 4 0 3 in the same manner as when encoding. The predicted image generation device 40 4 generates a predicted image from the blurred prediction reference frame. Then, the prediction residual which is the decoding result of the image decoding device 4101 and the prediction image are added, and the decoding is completed. When the frame being decoded is a P picture, the prediction reference frame blurring device 4 0 3 does not blur the prediction reference frame. The predicted image generation device 40 4 generates a predicted image, adds the decoded prediction residual and the predicted image, and completes decoding.

Industrial applicability:

INDUSTRIAL APPLICABILITY The present invention can be applied to a moving image processing apparatus that realizes encoding at a low bit rate in order to realize long-time recording to DVD and video distribution in a narrow communication network band.

Claims

1. In a video processing device that processes video consisting of consecutive video frames,

Blur intensity determining means for determining the intensity of blurring the video frame;

Blue

In accordance with the determination of the blur intensity determination means, the image blur means for blurring the image by removing the high-frequency signal of the video frame,

The blur intensity determining means changes the intensity of blurring when a predetermined number of video frames continue.

Surrounding

A moving image processing apparatus.

2. The blur intensity determination means changes the intensity of blurring periodically.

The moving image processing apparatus according to claim 1, wherein:

3. The moving image processing apparatus according to claim 1 or 2, wherein the blur intensity determining means changes the intensity to be blurred every other frame.

4. The blur intensity determining means determines the intensity to blur according to the change in pixel value between video frames.

The moving image processing apparatus according to any one of claims 1 to 3, wherein the apparatus is a moving image processing apparatus.

5. It comprises image encoding means for encoding the video frame output by the image blurring means,

The blur intensity determining means determines the intensity to be blurred according to the encoding method when the image encoding means encodes the video frame.

The moving image processing apparatus according to claim 3.

6. It comprises image encoding means for encoding the video frame output by the image blurring means,

The blur intensity determining means determines an intensity to be blurred according to an encoding method when the image encoding means encodes a video frame and a pixel value change between the video frames. The moving image processing apparatus according to claim 3.

7. local decoding means for decoding the video frame encoded by the image encoding means to generate a predicted reference frame ';

First storage means for storing the prediction reference frame; and

A prediction reference frame blurring unit that removes a high-frequency signal of the prediction reference frame; and a prediction image generation unit that generates a prediction image of motion compensated prediction from the prediction reference frame from which the prediction reference frame blurring unit has removed the high-frequency signal. ,

The prediction reference frame blurring unit removes the high frequency signal determined to be removed from the video frame by the blur intensity determination unit from the prediction reference frame;

The image encoding means encodes the result of the subtraction process between the video frame output from the image blurring means and the predicted image generated by the predicted image generating means.

7. The moving image processing apparatus according to claim 5 or claim 6, wherein

8. Decoding means for decoding the video frame encoded by the image encoding means, second storage means for storing the video frame decoded by the decoding means,

Second predicted image generation means for generating a predicted image of motion compensation prediction from the video frame stored in the second storage means;

The moving image according to claim 7, further comprising: an adding unit that adds and outputs the video frame decoded by the decoding unit and the predicted image generated by the second predicted image generating unit. Processing equipment.

9. Decoding means for decoding the video frame encoded by the image encoding means, second storage means for storing the video frame decoded by the decoding means,

A second prediction reference frame blurring unit that removes a high-frequency signal determined to be removed by the blur intensity determination unit from the video frame stored in the second storage unit; and Second predictive image generating means for generating a predictive image of motion compensation prediction from the video frame from which the signal is removed;

An adder for adding and outputting the video frame decoded by the decoding unit and the predicted image generated by the second predicted image generating unit;

8. The moving image processing apparatus according to claim 7, wherein

1 0. In a moving image processing apparatus for processing a moving image composed of continuous video frames,

For each video frame, it is determined whether or not to perform a fill process, and when it is determined that the filter process is performed, an in-loop fill process determining unit that determines a filter characteristic in the loop that performs the filter process;

An input image fill processing means for performing a fill evening process on the input video frame with a filter having characteristics determined by the in-loop filter determining means;

Image encoding means for encoding the filtered video frame;

Local decoding means for generating a prediction reference frame obtained by decoding the video frame encoded by the image encoding means;

First storage means for storing the predicted reference frame;

In-loop fill processing means for performing fill processing on the prediction reference frame with the fill of the characteristic determined by the in-loop filter determining means;

A prediction image generating means for generating a prediction image from the prediction reference frame subjected to the filtering process by the in-loop fill processing means;

The input image filter processing means and the in-loop filter processing means perform filter processing with a filter having the same characteristics as described above,

The image encoding unit encodes a result of a subtraction process between the video frame output from the input image filter processing unit and the predicted image generated by the predicted image generation unit.

A moving image processing apparatus.

1 1. Decoding means for decoding the encoded video frame;

The second storage means for storing the video frame decoded by the decoding means; and the video frame stored in the second storage means is subjected to filter processing with a filter having the characteristics determined by the in-loop filter determination means A second in-loop filtering means;

Second predictive image generating means for generating a predictive image for motion compensation prediction from the video frame in which the second in-loop filter processing means has performed the fill process; An adder for adding and outputting the video frame decoded by the decoding unit and the predicted image generated by the second predicted image generating unit;

The moving image processing apparatus according to claim 10, wherein:

1 2. In a moving image processing method for processing a moving image composed of continuous video frames,

A blur intensity determination step for determining the intensity of blurring the video frame;

In accordance with the determination in the blur intensity determination step, the image blur step of blurring the image by removing the high frequency signal of the video frame,

The blur intensity determining step includes a step of changing a blur intensity when a predetermined number of video frames continue.

And a moving image processing method.

1 3. The blur intensity determining step includes a step of periodically changing the intensity of blurring.

The moving image processing method according to claim 12, wherein:

1 4. The blur intensity determining step includes a step of changing the intensity to be blurred every other frame.

The moving image processing method according to claim 12 or claim 13 characterized by that.

15. The blur intensity determining step includes a step of determining the intensity to be blurred according to a change in pixel value between video frames.

The moving image processing method according to claim 14, wherein:

1 6. The image includes an image encoding step for encoding the video frame output in the blur step, and

15. The moving image processing method according to claim 14, wherein the blur intensity determining step includes a step of determining an intensity to be blurred in accordance with an encoding method when encoding a video frame in the image encoding step. .

1 7. An image encoding step for encoding the video frame output in the image blurring step is provided,

The blur intensity determination step encodes the video frame in the image encoding step. Determining the intensity to be blurred according to the encoding method and the change in pixel value between video frames.

The moving image processing method according to claim 14, wherein:

1 8. a local decoding step of decoding the video frame encoded in the image encoding step to generate a prediction reference frame;

A prediction reference frame blurring step for removing high frequency signals of the prediction reference frame;

A prediction image generation step of generating a prediction image of motion compensated prediction from a prediction reference frame from which a high-frequency signal has been removed in the prediction reference frame blur step;

Removing the high-frequency signal determined to be removed from the video frame in the blur intensity determining step from the predicted reference frame;

The image encoding step includes a step of encoding a result of a subtraction process between the video frame output in the image blurring step and the predicted image generated in the predicted image generation step.

The moving image processing method according to claim 16 or claim 17, wherein:

19. A decoding step for decoding the video frame encoded in the image encoding step, and a second prediction image generation step for generating a prediction image for motion compensated prediction from the video frame decoded in the decoding step. ,

An addition step of adding and outputting the video frame decoded in the decoding step and the prediction image generated in the second prediction image generation step

The moving image processing method according to claim 18, wherein:

A decoding step for decoding the video frame encoded in the image encoding step;

A second prediction reference frame blur step for removing the high-frequency signal determined to be removed in the blur intensity determination step from the video frame decoded in the decoding step; A second predictive image generating step of generating a predictive image of motion compensated prediction from a video frame from which a high-frequency signal has been removed in the second predictive reference frame blurring step; the video frame decoded in the decoding step; The moving image processing method according to claim 18, further comprising: an adding step of adding and outputting the predicted image generated in the second predicted image generating step.

2 1. In a moving image processing method for processing a moving image composed of continuous video frames,

For each video frame, it is determined whether or not to perform filter processing, and when it is determined that the filter processing is performed, an in-loop filter determining step for determining an in-loop filter characteristic for performing the filter processing;

An input image filter processing step for performing filtering on the input video frame with a fill of the characteristics determined in the in-loop fill determination step;

An image encoding step for encoding the filtered video frame; a local decoding step for generating a prediction reference frame obtained by decoding the video frame encoded in the image encoding step;

An in-loop fill processing step for filtering the prediction reference frame with the characteristic fill determined in the in-loop filter determining step;

A predictive image generating step for generating a predictive image from a predictive reference frame in which the fill-in-loop process step in the loop has performed the fill-in-process,

The input image filter processing step and the in-loop filter processing step are:

A step that performs filtering with a fill that has the same characteristics as above, and

The image encoding step includes a step of encoding a result of a subtraction process between the image frame output in the input image fill processing step and the predicted image generated in the predicted image generation step.

And a moving image processing method.

2 2. A decoding step for decoding the encoded video frame;

The in-loop fill determination step is added to the video frame decoded in the decoding step. A second loop in-loop processing step that performs filtering with the filter having the characteristics determined in

A second predicted image generation step for generating a predicted image for motion compensated prediction from the video frame subjected to the fill processing in the second in-loop filter processing step; the video frame decoded in the decoding step; An addition step for adding and outputting the prediction image generated in the second prediction image generation step.

The moving image processing method according to claim 21, wherein:

2 3. In a moving image processing program for causing a computer to execute a step of processing a moving image composed of continuous video frames,

The moving image processing step includes

An image blur step of blurring the image by removing the high frequency signal of the video frame according to the determination in the blur intensity determination step;

The blur intensity determining step includes a step of changing an intensity of blurring when a predetermined number of video frames continue.

A moving image processing program.

24. The moving image processing program according to claim 23, wherein the blur intensity determining step includes a step of periodically changing the intensity of blur. '

25. The moving image processing program according to claim 23, wherein the blur intensity determining step includes a step of changing an intensity to be blurred every other frame.

26. The moving image processing program according to claim 25, wherein the blur intensity determining step includes a step of determining an intensity to be blurred according to a change in pixel value between video frames.

2 7. An image encoding step for encoding the video frame output in the image blurring step is provided,

The blur intensity determining step includes a step of determining an intensity to be blurred according to an encoding method when encoding a video frame in the image encoding step. 26. The moving image processing program according to claim 25, wherein:

2 8. An image encoding step for encoding the video frame output in the image blurring step is provided,

The blur intensity determining step includes a step of determining an intensity to be blurred according to an encoding method used when encoding a video frame and a change in pixel value between the video frames in the image encoding step.

26. The moving image processing program according to claim 25, wherein:

29. a local decoding step for decoding the video frame encoded in the image encoding step to generate a prediction reference frame;

A predicted reference frame blurring step for removing high frequency signals of the predicted reference frame;

A prediction image generation step of generating a prediction image of motion compensated prediction from the prediction reference frame from which a high-frequency signal has been removed in the prediction reference frame blurring step, wherein the prediction reference frame blurring step comprises:

Removing the high frequency signal determined to be removed from the video frame in the blur intensity determining step from the predicted reference frame;

29. The moving image processing program according to claim 27 or claim 28, wherein:

A second prediction image generation step for generating a prediction image of motion compensation prediction from the video frame decoded in the decoding step;

30. The moving image processing program according to claim 29, wherein:

3 1. Decoding step for decoding the video frame encoded in the image encoding step. And

A second prediction reference frame blur step for removing the high-frequency signal determined to be removed in the blur intensity determination step from the video frame decoded in the decoding step;

A second predictive image generating step of generating a predictive image of motion compensated prediction from a video frame from which a high-frequency signal has been removed in the second predictive reference frame blurring step; the video frame decoded in the decoding step; An addition step for adding and outputting the prediction image generated in the second prediction image generation step.

30. The moving image processing program according to claim 29, wherein:

3 2. In a moving image processing program for causing a computer to execute a step of processing a moving image composed of continuous video frames,

For each video frame, it is determined whether or not to perform filter processing, and when it is determined to perform the filter processing, an in-loop filter determination step for determining an in-loop filter characteristic for performing the filter processing;

An input image filter processing step for performing fill image processing on the input video frame at the fill image with the characteristics determined in the in-loop fill image determination step;

An in-loop filter processing step for filtering the prediction reference frame with the characteristic fill determined in the in-loop filter determination step;

A predictive image generation step of generating a predictive image from the prediction reference frame in which the fill-in-loop processing step in the loop performs the fill-up process,

The input image filtering step and the in-loop filtering step are:

Filtering with a filter having the same characteristics as above,

The image encoding step includes a result of a subtraction process between the video frame output in the input image fill processing step and the predicted image generated in the predicted image generation step. Includes encoding the result

A moving image processing program.

3 3. a decoding step of decoding the encoded video frame;

A second in-loop filtering step for performing filtering on the video frame decoded in the decoding step with the fill factor of the characteristic determined in the in-loop fill factor determining step;

A second predicted image generating step of generating a predicted image of motion compensated prediction from the video frame filtered in the second in-loop filter processing step; the video frame decoded in the decoding step; An addition step for adding and outputting the prediction image generated in the second prediction image generation step.

The moving image processing program according to claim 32, characterized by that.