WO2013056129A1 - Region-based image compression - Google Patents

Region-based image compression Download PDF

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Publication number
WO2013056129A1
WO2013056129A1 PCT/US2012/060069 US2012060069W WO2013056129A1 WO 2013056129 A1 WO2013056129 A1 WO 2013056129A1 US 2012060069 W US2012060069 W US 2012060069W WO 2013056129 A1 WO2013056129 A1 WO 2013056129A1
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WIPO (PCT)
Prior art keywords
region
image
acceptability criteria
regions
compression
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PCT/US2012/060069
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French (fr)
Inventor
Andrew S. Pomianowski
Konstantine Iourcha
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Advanced Micro Devices, Inc.
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Publication date
Application filed by Advanced Micro Devices, Inc. filed Critical Advanced Micro Devices, Inc.
Priority to CN201280057403.9A priority Critical patent/CN103947206B/en
Priority to EP12778021.1A priority patent/EP2767085A1/en
Priority to KR1020147012735A priority patent/KR20140090999A/en
Priority to KR1020187018879A priority patent/KR20180080365A/en
Priority to JP2014535947A priority patent/JP2014532377A/en
Publication of WO2013056129A1 publication Critical patent/WO2013056129A1/en

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    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • G—PHYSICS
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    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4084—Scaling of whole images or parts thereof, e.g. expanding or contracting in the transform domain, e.g. fast Fourier transform [FFT] domain scaling
    • G—PHYSICS
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    • H04N19/12—Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
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    • H04N19/167—Position within a video image, e.g. region of interest [ROI]
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    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
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    • H04N19/192—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding the adaptation method, adaptation tool or adaptation type being iterative or recursive
    • H04N19/194—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding the adaptation method, adaptation tool or adaptation type being iterative or recursive involving only two passes
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    • H04N19/196—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding being specially adapted for the computation of encoding parameters, e.g. by averaging previously computed encoding parameters
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    • H—ELECTRICITY
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    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/154—Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion

Definitions

  • the present invention is generally directed to image compression and in particular, to a method for region-based image compression.
  • Lossy compression techniques require methods to effectively encode images at lower bit rates without sacrificing significant image quality.
  • Fixed rate compression schemes generally have poor image quality at rates significantly below four bits per pixel.
  • Some existing variable rate compression techniques like Joint Photographic Experts Group (JPEG), apply some form of transform and quantization.
  • Some methods of reducing the amount of data to be stored after compression may involve storing the data in a sparse manner and interpolating the results.
  • Existing methods generally have not provided good levels of image quality, and in some cases may also introduce potentially undesired image artifacts (e.g., high frequency noise).
  • Adding a local per-region transform and quantization step before subsequent compression steps may reduce the amount of data to be compressed, thereby reducing the required bit rate needed to maintain a high level of image quality.
  • a reconstruction transformation is applied to generate the pixel values.
  • a method for compressing an image includes decomposing the image into one or more regions.
  • a region of the image is selected to be evaluated.
  • the selected region is transformed and quantized if the region does not meet a predetermined compression acceptability criteria.
  • the predetermined compression acceptability criteria may include a specific bit rate, a specific image quality, or combinations thereof. If the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized, then the transformation and quantization settings are adjusted and the region is transformed and quantized using the adjusted settings.
  • the region is then encoded when the predetermined compression acceptability criteria has been reached.
  • a method for compressing an image includes decomposing the image into one or more regions.
  • a region of the image is selected to be evaluated.
  • the selected region is decomposed into subregions.
  • the subregions are transformed and quantized if the region does not meet a predetermined compression acceptability criteria. If the region does not meet the predetermined compression acceptability criteria based on a combination of subregion split, transform, and quantization, then the subregion split is adjusted and the adjusted subregion is transformed and quantized.
  • the region is then encoded when the predetermined compression acceptability criteria has been reached.
  • a method for decompressing an image, the image including one or more regions includes selecting a region of the image to decode. The selected region and metadata associated with the selected region are decoded. A reconstruction transformation is applied to the selected region, wherein the metadata includes information regarding the reconstruction transformation.
  • a method for decompressing an image including one or more regions, each of which includes one or more subregions.
  • a region of the image is selected to be decompressed.
  • the selected region and metadata associated with the selected region are decoded.
  • Reconstruction transformations are applied to each of the subregions in the selected region, wherein the metadata includes information regarding the reconstruction transformations.
  • a system for compressing an image includes an encoder.
  • the encoder is configured to decompose the image into one or more regions, select a region of the image to evaluate, and transform and quantize the region if the region does not meet a predetermined compression acceptability criteria. If the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized, the encoder is further configured to adjust the transformation and quantization settings, and transform and quantize the region using the adjusted settings. The region is then encoded when the predetermined compression acceptability criteria has been reached.
  • a system for decompressing an image includes a decoder.
  • the decoder is configured to select a region of the image to decode, decode the selected region and metadata associated with the selected region, and apply a reconstruction transformation to the selected region, wherein the metadata includes information regarding the reconstruction transformation.
  • a non-transitory computer-readable storage medium storing a set of instructions for execution by a general purpose computer to compress an image includes a decomposing code segment, a selecting code segment, a transforming and quantizing code segment, an adjusting code segment, and an encoding code segment.
  • the decomposing code segment is for decomposing the image into one or more regions.
  • the selecting code segment is for selecting a region of the image to evaluate.
  • the transforming and quantizing code segment is for transforming and quantizing the region if the region does not meet a predetermined compression acceptability criteria.
  • the adjusting code segment is for adjusting the transformation and quantization settings if the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized.
  • a method for compressing an image includes decomposing the image into one or more regions.
  • a region is selected, and is split into one or more subregions.
  • a subregion, one of a plurality of transforms, and one of a plurality of quantizers are selected.
  • the selected subregion split, transform, and quantizer are evaluated against a predetermined compression acceptability criteria.
  • Each of the subregions, the subregion splits, the transforms, and the quantizers are iteratively selected to determine a best subregion split, transform, and quantizer in terms of the predetermined compression acceptability criteria. All of the subregions are encoded using the best subregion split, transform, and quantizer when the predetermined compression acceptability criteria has been reached.
  • a method for compressing an image includes decomposing the image into one or more regions.
  • a region of the image is selected to be evaluated.
  • the selected region is compressed, and is transformed and quantized if the compressed region does not meet a predetermined compression acceptability criteria. If the transformed and quantized region does not meet the predetermined compression acceptability criteria after it has been transformed and quantized, then the transformation and quantization settings are adjusted.
  • the compressed region is transformed and quantized using the adjusted settings.
  • the transformed and quantized region is encoded when the predetermined compression acceptability criteria has been reached.
  • Figure 1 is a block diagram of an example device in which one or more disclosed embodiments may be implemented
  • Figure 2 is a flow chart of a method for compressing an image
  • Figure 3 is a flow chart of an alternate method for compressing an image
  • Figure 4 is a flow chart of a method for decompressing a region of an image
  • Figure 5 is a flow chart of a method for compressing an image that evaluates combinations of transforms and quantizers.
  • FIG. 1 is a block diagram of an example device 100 in which one or more disclosed embodiments may be implemented.
  • the device 100 may include, for example, a computer, a gaming device, a handheld device, a set-top box, a television, a mobile phone, or a tablet computer.
  • the device 100 includes a processor 102, a memory 104, a storage 106, one or more input devices 108, and one or more output devices 110.
  • the device 100 may also optionally include an input driver 112 and an output driver 114. It is understood that the device 100 may include additional components not shown in Figure 1.
  • the processor 102 may include a central processing unit (CPU), a graphics processing unit (GPU), a CPU and GPU located on the same die, or one or more processor cores, wherein each processor core may be a CPU or a GPU.
  • the memory 104 may be located on the same die as the processor 102, or may be located separately from the processor 102.
  • the memory 104 may include a volatile or non-volatile memory, for example, random access memory (RAM), dynamic RAM, or a cache.
  • the storage 106 may include a fixed or removable storage, for example, a hard disk drive, a solid state drive, an optical disk, or a flash drive.
  • the input devices 108 may include a keyboard, a keypad, a touch screen, a touch pad, a detector, a microphone, an accelerometer, a gyroscope, a biometric scanner, or a network connection (e.g., a wireless local area network card for transmission and/or reception of wireless IEEE 802 signals).
  • the output devices 110 may include a display, a speaker, a printer, a haptic feedback device, one or more lights, an antenna, or a network connection (e.g., a wireless local area network card for transmission and/or reception of wireless IEEE 802 signals).
  • the input driver 112 communicates with the processor 102 and the input devices 108, and permits the processor 102 to receive input from the input devices 108.
  • the output driver 114 communicates with the processor 102 and the output devices 110, and permits the processor 102 to send output to the output devices 110. It is noted that the input driver 112 and the output driver 114 are optional components, and that the device 100 will operate in the same manner if the input driver 112 and the output driver 114 are not present.
  • Figure 2 is a flow chart of a method 200 for compressing an image.
  • An image to be encoded is selected (step 202) and the selected image is decomposed into several regions according to a predetermined method (step 204).
  • the regions may be a fixed size or a variable size, and the decomposing method may be hierarchical. It is noted that the particular method used to decompose the image into regions does not affect the overall operation of the method 200.
  • a region is selected for evaluation (step 206) and is examined to determine if the region meets a predetermined compression acceptability criteria (step 208).
  • the predetermined compression acceptability criteria may include, but is not limited to, a specific bit rate, a specific image quality, or combinations thereof. It may be possible to encode the region to meet the predetermined compression acceptability criteria using the basic underlying compression system. In this case, no additional transform and quantization step is required, and the region can be processed directly in the encoding stage. This may be viewed as a special case where the transform is the identity transform.
  • the region does not meet the predetermined compression acceptability criteria (step 208), then several refinements may be performed.
  • the region is transformed and quantized (step 210). If the method determines that the region needs to be transformed and quantized to satisfy predefined compression acceptability criteria, then the method selects the transform and quantization from a predefined set.
  • the set may include only linear transforms, for example filtering with a smoothing kernel, wavelet transforms, curvelet transforms, Gabor wavelet transforms, etc. In another embodiment, the set may include non-linear transforms.
  • the encoder may evaluate multiple potential combinations of transform and quantization, selecting the combination that achieves the highest quality at the predetermined compression acceptability criteria.
  • the encoder may have parameters to control the extent of any optimization steps at this stage to tradeoff overall compression quality against encoding performance. These controls may limit the extent of the search for optimal transforms and quantizations, and may also provide threshold values, permitting the technique to exit early when certain targets are reached.
  • Quantization is performed by taking the coefficients output from the transform and rounding them to a predefined set of values, and the set may be different for each coefficient.
  • sets of the values corresponding to some of the coefficients may consist of a single value of zero, which means that the corresponding coefficients are discarded (such as in downsampling). After quantization, the remaining coefficients are encoded.
  • the region is encoded (step 216).
  • the encoding may incorporate some underlying compression.
  • the output data format includes some metadata to be stored and/or transmitted with the region, to indicate the transform and the quantization applied for that region and other information that may be required for decoding.
  • the encoded region may be transmitted (not shown in Figure 2). If all of the regions of the image have not been examined (step 218), then the method continues by selecting another region to evaluate (step 206). If all of the regions of the image have been examined (step 218), then the method terminates.
  • the transform and quantization in step 210 may be configured to be a downscaling operation.
  • a region that is to be compressed is evaluated and downscaled with a selected aspect ratio (which encompasses the transform and quantization) prior to compression, to reduce the total number of pixels in the region while retaining as much of the information as possible.
  • Performing the downscaling reduces the amount of data prior to encoding, allowing the encoding (which may include additional compression steps) to occur with a higher accuracy for a given bit rate.
  • One of a set of different aspect ratios may be selected for downscaling the region.
  • the selected aspect ratio provides the best results according to a selected error metric (for example, peak signal to noise ratio) by evaluating the results of quantizing to each possible ratio against this metric for the current region.
  • the target bit rate is known (for example, in a fixed-rate compression scheme), and the amount of space available at the target bit rate can be calculated.
  • this information there may be multiple ways a region could be scaled to fit in the available space.
  • some of the high-frequency image information is discarded, effectively blurring the region.
  • the choice of the scaling aspect ratio may have a significant impact on preserving the image quality.
  • By applying a non-uniform scaling to the original data more of the important information in the original image can be preserved.
  • the compression can respond to local characteristics in the image content for different regions.
  • the implementation may potentially examine multiple possible choices of transform and quantization for each region in the image to optimize the predetermined compression acceptability criteria.
  • FIG. 3 is a flow chart of an alternate method 300 for compressing an image.
  • An image to be encoded is selected (step 302) and the selected image is decomposed into several regions according to a predetermined method (step 304).
  • the regions may be a fixed size or a variable size, and the decomposing method may be hierarchical. It is noted that the particular method used to decompose the image into regions does not affect the overall operation of the method 300.
  • a region is selected for evaluation (step 306) and is examined to determine if the region meets a predetermined compression acceptability criteria (step 308).
  • the predetermined compression acceptability criteria may include, but is not limited to, a specific bit rate, a specific image quality, or combinations thereof. It may be possible to encode the region to meet the predetermined compression acceptability criteria using the basic underlying compression system. In this case, no transform and quantization step is required, and the region can be processed by the underlying compression scheme. This may be viewed as a special case where the transform is the identity transform.
  • the region does not meet the predetermined compression acceptability criteria (step 308), then several refinements may be performed.
  • the region is split into subregions (step 310), and the subregions are transformed and quantized (step 312). If the encoder determines that the region needs to be split, transformed, and quantized to satisfy the predetermined compression acceptability criteria, then the encoder selects a split, transform, and quantization from a set of predefined splits, transforms, and quantizations.
  • the set may include only linear transforms, for example filtering with a smoothing kernel, wavelet transforms, curvelet transforms, Gabor wavelet transforms, etc. In another embodiment, the set may include nonlinear transforms.
  • the encoder may evaluate multiple potential combinations of region split (how the region is split into subregions), transform, and quantization, selecting the combination that achieves the highest quality to meet the predetermined compression acceptability criteria.
  • the encoder may have parameters to control the extent of any optimization steps at this stage to tradeoff overall compression quality against encoding performance. These controls may limit the extent of the search for optimal regions, subregion splits, transforms, and quantizations, and may also provide threshold values, permitting the technique to exit early when certain targets are reached.
  • step 314 It is then determined whether the region meets the predetermined compression acceptability criteria based on a combination of split, transform, and quantization (step 314). If the region does not meet the predetermined compression acceptability criteria, then the split (how the region is split into subregions), transform, and/or quantization may be adjusted (step 316) and the adjusted subregions are transformed and quantized (step 312) based on the adjustment(s). If the split is adjusted (step 316), a different splitting technique may be used to generate alternative region splits that may result in achieving the predetermined compression acceptability criteria.
  • the region is encoded (step 318).
  • the encoding may incorporate some underlying compression.
  • the output data format includes some metadata to be stored and/or transmitted with the region, to indicate the region split, the transform, and the quantization applied for that region and other information that may be required for decoding.
  • the encoded region may be transmitted (not shown in Figure 3). If all of the regions of the image have not been examined (step 320), then the method continues by selecting another region to evaluate (step 306). If all of the regions of the image have been examined (step 320), then the method terminates.
  • Figure 4 is a flow chart of a method 400 for decompressing a region of an image.
  • a region of the image is selected for decoding (step 402), and the selected region and its associated metadata are decoded (step 404).
  • a reconstruction transformation is applied to the region using information included in the metadata (step 406).
  • Additional processing is then performed on the region as needed prior to displaying the image (step 408). Examples of the additional processing may include, for example, texture mapping operations, etc.
  • the region maybe split into subregions.
  • the subregions may share a single transform and quantization (specified for the whole region), or each subregion may have its own individual transform and quantization specified.
  • step 406 may be an upscaling operation, if the region was downscaled during encoding.
  • the data is expanded according to the underlying compression method for the region.
  • the region is then upscaled using information included in the metadata describing the aspect ratio used for the downscaling (step 406).
  • the upscaling may use any applicable filter, but to preserve image quality, the encoder needs to know what filter will be used by the decoder, as this allows the compression quality to be tuned more precisely.
  • the upscaling filter may be bilinear, because this filter is simple and cheap to implement. Other types of upscaling filters may be used without substantially altering the operation of the method 400.
  • the type of filter used for upscaling may be uniform over the entire image or may be selected independently for each region of the image.
  • the encoder uses a fixed- rate region-based compression scheme with a given region size, e.g., 8x8.
  • a given region size e.g. 8x8.
  • Each region is compressed independently. If it is not possible to encode every pixel in the region explicitly at the required bit rate, then the region is downscaled by a predetermined ratio prior to compression. For example, the 8x8 region may be reduced in size to 8x6, which would reduce the amount of pixel information that needs to be stored by 25%. The level of information reduction is chosen to allow the region to be encoded at the desired compression acceptability criteria.
  • the downscaling may be accomplished by any appropriate method, with higher quality methods being used to retain more useful information.
  • the encoder may try different ratios, and use the ratio that provides the best image quality in terms of the predetermined compression acceptability criteria (selecting from the multiple different quantizations).
  • the method may choose to use a higher level of downscaling (e.g., 8x5, 8x4, 6x5, etc.) and evaluate these ratios in conjunction with the encoder using back-end compression schemes that have a lower compression rate.
  • a higher level of downscaling e.g., 8x5, 8x4, 6x5, etc.
  • the remaining pixels may be encoded with a higher accuracy (i.e., a lower compression rate), while achieving the same predetermined compression acceptability criteria.
  • One extension to this embodiment is to downsample information along a selected vector direction, to preserve more of the image quality in the region (rather than the approximation achieved using downsampling aligned to the X and Y axes but with a variable aspect ratio).
  • the quantization could be the same as above, but the transform is now different.
  • This extension may allow better preservation of detail in regions of the image where the high frequency content is aligned closer to the diagonals. For example, if an image can be downscaled with knowledge of the direction of motion in the image (if any), then the high-frequency information orthogonal to the direction of the motion can be retained, while other information may be discarded.
  • a second extension to this embodiment is to subdivide the original region further into subregions, and independently scale each subregion (select a different transform and quantization for each subset) to better match the characteristics of the region to provide a higher image quality.
  • FIG. 5 is a flow chart of a method 500 for compressing an image that evaluates combinations of regions, subregions, transforms, and quantizers.
  • An image to be encoded is selected (step 502) and the selected image is decomposed into regions (step 504).
  • a region of the image is selected (step 506).
  • the selected region is split into subregions (step 508), a subregion is selected (step 510), a transform is selected (step 512), and a quantizer is selected (step 514).
  • the selected subregion of the image is processed and evaluated to determine whether it meets predetermined compression acceptability criteria (step 516).
  • the selection of the split (step 508), transform (step 512), and quantizer (step 514) may be performed in any order without affecting the overall operation of the method 500.
  • the compression acceptability criteria that are determined by the selected subregion split, transform, and quantizer may be stored for later comparison.
  • step 518 If all of the quantizers have not been evaluated or a threshold compression acceptability criteria has not been reached (step 518), then another quantizer is selected (step 514) and processing continues as described above. If all of the quantizers have been evaluated or if the threshold compression acceptability criteria has been reached (step 518), then a determination is made whether all of the transforms have been evaluated or the threshold compression acceptability criteria has been reached (step 520).
  • step 520 If all of the transforms have not been evaluated or the threshold compression acceptability criteria has not been reached (step 520), then another transform is selected (step 512) and processing continues as described above. If all of the transforms have been evaluated or the threshold compression acceptability criteria has been reached (step 520), then a determination is made whether all subregions have been evaluated (step 522).
  • step 522) then another subregion of the region is selected (step 510) and processing continues as described above. If all of the subregions have been evaluated (step 522), then a determination is made whether all of the subregion splits have been evaluated or the threshold compression acceptability criteria has been reached (step 524).
  • step 524 If all of the subregion splits have not been evaluated and the threshold compression acceptability criteria has not been reached (step 524), then the region is split into different subregions (step 508) and processing continues as described above. In an alternative embodiment (not shown), the threshold compression acceptability criteria defined in steps 518, 520, and 524 may not be used.
  • the best splits, transforms, and quantizers are selected (step 526). All of the subregions of the region are encoded using the best subregion splits, transforms, and quantizers (step 528). In one implementation, the encoding in step 528 may also include additional compression.
  • the output data format includes some metadata to be stored and/or transmitted with the region, to indicate the subregion splits, transforms, and quantizers applied for that region and other information that may be required for decoding.
  • step 530 a determination is made whether all of the regions of the image have been examined. If all of the regions of the image have not been examined, then another region of the image is selected (step 506) and processing continues as described above. If all of the regions of the image have been examined (step 530), then the method terminates.
  • texture filtering operations will be performed on the decoded data, so an upscaling filter may be implemented by manipulating the texture filtering hardware, rather than by implementing an additional dedicated upscaler.
  • the (encoding) generates index coefficients that are used to select colors.
  • the transformation and quantization may be performed on the index coefficients produced by the underlying encoder, rather than on the original color data.
  • the region is compressed prior to the region being transformed and quantized.
  • processors include, by way of example, a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), and/or a state machine.
  • DSP digital signal processor
  • ASICs Application Specific Integrated Circuits
  • FPGAs Field Programmable Gate Arrays
  • Such processors may be manufactured by configuring a manufacturing process using the results of processed hardware description language (HDL) instructions and other intermediary data including netlists (such instructions capable of being stored on a computer readable media).
  • HDL hardware description language
  • netlists such instructions capable of being stored on a computer readable media.
  • the results of such processing may be maskworks that are then used in a semiconductor manufacturing process to manufacture a processor which implements aspects of the present invention.
  • non-transitory computer-readable storage medium for execution by a general purpose computer or a processor.
  • non-transitory computer-readable storage mediums include a read only memory (ROM), a random access memory (RAM), a register, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks, and digital versatile disks (DVDs).

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Abstract

A method for compressing an image includes decomposing the image into one or more regions. A region of the image is selected to be evaluated. The selected region is transformed and quantized if the region does not meet a predetermined compression acceptability criteria. The predetermined compression acceptability criteria may include a specific bit rate, a specific image quality, or combinations thereof. If the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized, then the transformation and quantization settings are adjusted and the region is transformed and quantized using the adjusted settings. The region is then encoded when the predetermined compression acceptability criteria has been reached. The encoding may include additional compression stages.

Description

REGION-BASED IMAGE COMPRESSION
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. provisional application
No. 61/547,648 filed October 14, 2011 and U.S. nonprovisional application No. 13/651,020 filed October 12, 2012, the contents of which are hereby incorporated by reference as if fully set forth herein.
FIELD OF INVENTION
[0002] The present invention is generally directed to image compression and in particular, to a method for region-based image compression.
BACKGROUND
[0003] Lossy compression techniques require methods to effectively encode images at lower bit rates without sacrificing significant image quality. Fixed rate compression schemes generally have poor image quality at rates significantly below four bits per pixel. Some existing variable rate compression techniques, like Joint Photographic Experts Group (JPEG), apply some form of transform and quantization.
[0004] Some methods of reducing the amount of data to be stored after compression may involve storing the data in a sparse manner and interpolating the results. Existing methods generally have not provided good levels of image quality, and in some cases may also introduce potentially undesired image artifacts (e.g., high frequency noise).
SUMMARY OF EMBODIMENTS
[0005] Adding a local per-region transform and quantization step before subsequent compression steps may reduce the amount of data to be compressed, thereby reducing the required bit rate needed to maintain a high level of image quality. During decompression, a reconstruction transformation is applied to generate the pixel values. Overall, performing a per-region transform and quantization permits better tradeoffs to be made in attaining low bit rates with high image quality, without adding unmanageable complexity to the image decoding.
[0006] A method for compressing an image includes decomposing the image into one or more regions. A region of the image is selected to be evaluated. The selected region is transformed and quantized if the region does not meet a predetermined compression acceptability criteria. The predetermined compression acceptability criteria may include a specific bit rate, a specific image quality, or combinations thereof. If the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized, then the transformation and quantization settings are adjusted and the region is transformed and quantized using the adjusted settings. The region is then encoded when the predetermined compression acceptability criteria has been reached.
[0007] A method for compressing an image includes decomposing the image into one or more regions. A region of the image is selected to be evaluated. The selected region is decomposed into subregions. The subregions are transformed and quantized if the region does not meet a predetermined compression acceptability criteria. If the region does not meet the predetermined compression acceptability criteria based on a combination of subregion split, transform, and quantization, then the subregion split is adjusted and the adjusted subregion is transformed and quantized. The region is then encoded when the predetermined compression acceptability criteria has been reached.
[0008] A method for decompressing an image, the image including one or more regions, includes selecting a region of the image to decode. The selected region and metadata associated with the selected region are decoded. A reconstruction transformation is applied to the selected region, wherein the metadata includes information regarding the reconstruction transformation.
[0009] A method for decompressing an image, the image including one or more regions, each of which includes one or more subregions. A region of the image is selected to be decompressed. The selected region and metadata associated with the selected region are decoded. Reconstruction transformations are applied to each of the subregions in the selected region, wherein the metadata includes information regarding the reconstruction transformations.
[0010] A system for compressing an image includes an encoder. The encoder is configured to decompose the image into one or more regions, select a region of the image to evaluate, and transform and quantize the region if the region does not meet a predetermined compression acceptability criteria. If the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized, the encoder is further configured to adjust the transformation and quantization settings, and transform and quantize the region using the adjusted settings. The region is then encoded when the predetermined compression acceptability criteria has been reached.
[0011] A system for decompressing an image, the image including one or more regions, includes a decoder. The decoder is configured to select a region of the image to decode, decode the selected region and metadata associated with the selected region, and apply a reconstruction transformation to the selected region, wherein the metadata includes information regarding the reconstruction transformation.
[0012] A non-transitory computer-readable storage medium storing a set of instructions for execution by a general purpose computer to compress an image, includes a decomposing code segment, a selecting code segment, a transforming and quantizing code segment, an adjusting code segment, and an encoding code segment. The decomposing code segment is for decomposing the image into one or more regions. The selecting code segment is for selecting a region of the image to evaluate. The transforming and quantizing code segment is for transforming and quantizing the region if the region does not meet a predetermined compression acceptability criteria. The adjusting code segment is for adjusting the transformation and quantization settings if the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized. The encoding code segment is for encoding the region when the predetermined compression acceptability criteria has been reached. [0013] A method for compressing an image includes decomposing the image into one or more regions. A region is selected, and is split into one or more subregions. A subregion, one of a plurality of transforms, and one of a plurality of quantizers are selected. The selected subregion split, transform, and quantizer are evaluated against a predetermined compression acceptability criteria. Each of the subregions, the subregion splits, the transforms, and the quantizers are iteratively selected to determine a best subregion split, transform, and quantizer in terms of the predetermined compression acceptability criteria. All of the subregions are encoded using the best subregion split, transform, and quantizer when the predetermined compression acceptability criteria has been reached.
[0014] A method for compressing an image includes decomposing the image into one or more regions. A region of the image is selected to be evaluated. The selected region is compressed, and is transformed and quantized if the compressed region does not meet a predetermined compression acceptability criteria. If the transformed and quantized region does not meet the predetermined compression acceptability criteria after it has been transformed and quantized, then the transformation and quantization settings are adjusted. The compressed region is transformed and quantized using the adjusted settings. The transformed and quantized region is encoded when the predetermined compression acceptability criteria has been reached.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings, wherein:
[0016] Figure 1 is a block diagram of an example device in which one or more disclosed embodiments may be implemented;
[0017] Figure 2 is a flow chart of a method for compressing an image;
[0018] Figure 3 is a flow chart of an alternate method for compressing an image; [0019] Figure 4 is a flow chart of a method for decompressing a region of an image; and
[0020] Figure 5 is a flow chart of a method for compressing an image that evaluates combinations of transforms and quantizers.
DETAILED DESCRIPTION
[0021] Fixed-rate block-based compression techniques require methods to effectively encode images at low bit rates without sacrificing significant image quality. Adding a local per-region transform and quantization step in front of any subsequent encoding and/or compression steps reduces the amount of data to be encoded and/or compressed to retain image quality while achieving a desired target bit rate. To decompress the region, the compressed data may first be fully or partially decompressed according to the underlying compression scheme (depending on the implementation). The reconstruction transformation is then applied to produce the approximation to the original uncompressed data. If any coefficients were discarded during quantization, those coefficients are assumed to be zero for the purposes of the reconstruction transformation.
[0022] Figure 1 is a block diagram of an example device 100 in which one or more disclosed embodiments may be implemented. The device 100 may include, for example, a computer, a gaming device, a handheld device, a set-top box, a television, a mobile phone, or a tablet computer. The device 100 includes a processor 102, a memory 104, a storage 106, one or more input devices 108, and one or more output devices 110. The device 100 may also optionally include an input driver 112 and an output driver 114. It is understood that the device 100 may include additional components not shown in Figure 1.
[0023] The processor 102 may include a central processing unit (CPU), a graphics processing unit (GPU), a CPU and GPU located on the same die, or one or more processor cores, wherein each processor core may be a CPU or a GPU. The memory 104 may be located on the same die as the processor 102, or may be located separately from the processor 102. The memory 104 may include a volatile or non-volatile memory, for example, random access memory (RAM), dynamic RAM, or a cache.
[0024] The storage 106 may include a fixed or removable storage, for example, a hard disk drive, a solid state drive, an optical disk, or a flash drive. The input devices 108 may include a keyboard, a keypad, a touch screen, a touch pad, a detector, a microphone, an accelerometer, a gyroscope, a biometric scanner, or a network connection (e.g., a wireless local area network card for transmission and/or reception of wireless IEEE 802 signals). The output devices 110 may include a display, a speaker, a printer, a haptic feedback device, one or more lights, an antenna, or a network connection (e.g., a wireless local area network card for transmission and/or reception of wireless IEEE 802 signals).
[0025] The input driver 112 communicates with the processor 102 and the input devices 108, and permits the processor 102 to receive input from the input devices 108. The output driver 114 communicates with the processor 102 and the output devices 110, and permits the processor 102 to send output to the output devices 110. It is noted that the input driver 112 and the output driver 114 are optional components, and that the device 100 will operate in the same manner if the input driver 112 and the output driver 114 are not present.
[0026] Figure 2 is a flow chart of a method 200 for compressing an image.
An image to be encoded is selected (step 202) and the selected image is decomposed into several regions according to a predetermined method (step 204). The regions may be a fixed size or a variable size, and the decomposing method may be hierarchical. It is noted that the particular method used to decompose the image into regions does not affect the overall operation of the method 200.
[0027] A region is selected for evaluation (step 206) and is examined to determine if the region meets a predetermined compression acceptability criteria (step 208). The predetermined compression acceptability criteria may include, but is not limited to, a specific bit rate, a specific image quality, or combinations thereof. It may be possible to encode the region to meet the predetermined compression acceptability criteria using the basic underlying compression system. In this case, no additional transform and quantization step is required, and the region can be processed directly in the encoding stage. This may be viewed as a special case where the transform is the identity transform.
[0028] If the region does not meet the predetermined compression acceptability criteria (step 208), then several refinements may be performed. The region is transformed and quantized (step 210). If the method determines that the region needs to be transformed and quantized to satisfy predefined compression acceptability criteria, then the method selects the transform and quantization from a predefined set. In one embodiment, the set may include only linear transforms, for example filtering with a smoothing kernel, wavelet transforms, curvelet transforms, Gabor wavelet transforms, etc. In another embodiment, the set may include non-linear transforms.
[0029] As part of its optimization procedure, the encoder may evaluate multiple potential combinations of transform and quantization, selecting the combination that achieves the highest quality at the predetermined compression acceptability criteria. The encoder may have parameters to control the extent of any optimization steps at this stage to tradeoff overall compression quality against encoding performance. These controls may limit the extent of the search for optimal transforms and quantizations, and may also provide threshold values, permitting the technique to exit early when certain targets are reached.
[0030] Quantization is performed by taking the coefficients output from the transform and rounding them to a predefined set of values, and the set may be different for each coefficient. In some embodiments, sets of the values corresponding to some of the coefficients may consist of a single value of zero, which means that the corresponding coefficients are discarded (such as in downsampling). After quantization, the remaining coefficients are encoded.
[0031] It is then determined whether the region meets the predetermined compression acceptability criteria based on a combination of transform and quantization (step 212). If the region does not meet the predetermined compression acceptability criteria, then the transform and quantization settings may be adjusted (step 214) and the adjusted region is transformed and quantized with the adjusted settings (step 210). [0032] After optimizing the transformation and quantization, and the region meets the predetermined compression acceptability criteria or all candidate settings have been evaluated and the best settings are chosen (steps 208 or 212), the region is encoded (step 216). The encoding may incorporate some underlying compression. For each region, the output data format includes some metadata to be stored and/or transmitted with the region, to indicate the transform and the quantization applied for that region and other information that may be required for decoding. In addition, the encoded region may be transmitted (not shown in Figure 2). If all of the regions of the image have not been examined (step 218), then the method continues by selecting another region to evaluate (step 206). If all of the regions of the image have been examined (step 218), then the method terminates.
[0033] In a specific implementation of the method 200 (not shown), the transform and quantization in step 210 may be configured to be a downscaling operation. A region that is to be compressed is evaluated and downscaled with a selected aspect ratio (which encompasses the transform and quantization) prior to compression, to reduce the total number of pixels in the region while retaining as much of the information as possible. Performing the downscaling reduces the amount of data prior to encoding, allowing the encoding (which may include additional compression steps) to occur with a higher accuracy for a given bit rate. One of a set of different aspect ratios may be selected for downscaling the region. The selected aspect ratio provides the best results according to a selected error metric (for example, peak signal to noise ratio) by evaluating the results of quantizing to each possible ratio against this metric for the current region.
[0034] In one implementation, the target bit rate is known (for example, in a fixed-rate compression scheme), and the amount of space available at the target bit rate can be calculated. With this information, there may be multiple ways a region could be scaled to fit in the available space. During downscaling, some of the high-frequency image information is discarded, effectively blurring the region. Depending on the content of the original region, the choice of the scaling aspect ratio may have a significant impact on preserving the image quality. By applying a non-uniform scaling to the original data, more of the important information in the original image can be preserved. By having a different level of scaling for each region, the compression can respond to local characteristics in the image content for different regions. The implementation may potentially examine multiple possible choices of transform and quantization for each region in the image to optimize the predetermined compression acceptability criteria.
[0035] Figure 3 is a flow chart of an alternate method 300 for compressing an image. An image to be encoded is selected (step 302) and the selected image is decomposed into several regions according to a predetermined method (step 304). The regions may be a fixed size or a variable size, and the decomposing method may be hierarchical. It is noted that the particular method used to decompose the image into regions does not affect the overall operation of the method 300.
[0036] A region is selected for evaluation (step 306) and is examined to determine if the region meets a predetermined compression acceptability criteria (step 308). The predetermined compression acceptability criteria may include, but is not limited to, a specific bit rate, a specific image quality, or combinations thereof. It may be possible to encode the region to meet the predetermined compression acceptability criteria using the basic underlying compression system. In this case, no transform and quantization step is required, and the region can be processed by the underlying compression scheme. This may be viewed as a special case where the transform is the identity transform.
[0037] If the region does not meet the predetermined compression acceptability criteria (step 308), then several refinements may be performed. The region is split into subregions (step 310), and the subregions are transformed and quantized (step 312). If the encoder determines that the region needs to be split, transformed, and quantized to satisfy the predetermined compression acceptability criteria, then the encoder selects a split, transform, and quantization from a set of predefined splits, transforms, and quantizations. In one embodiment, the set may include only linear transforms, for example filtering with a smoothing kernel, wavelet transforms, curvelet transforms, Gabor wavelet transforms, etc. In another embodiment, the set may include nonlinear transforms.
[0038] As part of its optimization procedure, the encoder may evaluate multiple potential combinations of region split (how the region is split into subregions), transform, and quantization, selecting the combination that achieves the highest quality to meet the predetermined compression acceptability criteria. The encoder may have parameters to control the extent of any optimization steps at this stage to tradeoff overall compression quality against encoding performance. These controls may limit the extent of the search for optimal regions, subregion splits, transforms, and quantizations, and may also provide threshold values, permitting the technique to exit early when certain targets are reached.
[0039] It is then determined whether the region meets the predetermined compression acceptability criteria based on a combination of split, transform, and quantization (step 314). If the region does not meet the predetermined compression acceptability criteria, then the split (how the region is split into subregions), transform, and/or quantization may be adjusted (step 316) and the adjusted subregions are transformed and quantized (step 312) based on the adjustment(s). If the split is adjusted (step 316), a different splitting technique may be used to generate alternative region splits that may result in achieving the predetermined compression acceptability criteria.
[0040] After optimizing the region split, transformation, and quantization, and the region meets the predetermined compression acceptability criteria and/or other termination conditions for this processing (steps 308 or 314), the region is encoded (step 318). The encoding may incorporate some underlying compression. For each region, the output data format includes some metadata to be stored and/or transmitted with the region, to indicate the region split, the transform, and the quantization applied for that region and other information that may be required for decoding. In addition, the encoded region may be transmitted (not shown in Figure 3). If all of the regions of the image have not been examined (step 320), then the method continues by selecting another region to evaluate (step 306). If all of the regions of the image have been examined (step 320), then the method terminates.
[0041] Figure 4 is a flow chart of a method 400 for decompressing a region of an image. A region of the image is selected for decoding (step 402), and the selected region and its associated metadata are decoded (step 404). A reconstruction transformation is applied to the region using information included in the metadata (step 406). Additional processing is then performed on the region as needed prior to displaying the image (step 408). Examples of the additional processing may include, for example, texture mapping operations, etc.
[0042] In an alternate embodiment of the method 400 (not shown) the region maybe split into subregions. The subregions may share a single transform and quantization (specified for the whole region), or each subregion may have its own individual transform and quantization specified.
[0043] In an alternate embodiment of the method 400 (not shown), step 406 may be an upscaling operation, if the region was downscaled during encoding. The data is expanded according to the underlying compression method for the region. The region is then upscaled using information included in the metadata describing the aspect ratio used for the downscaling (step 406). The upscaling may use any applicable filter, but to preserve image quality, the encoder needs to know what filter will be used by the decoder, as this allows the compression quality to be tuned more precisely. In a hardware implementation, the upscaling filter may be bilinear, because this filter is simple and cheap to implement. Other types of upscaling filters may be used without substantially altering the operation of the method 400. In addition, the type of filter used for upscaling may be uniform over the entire image or may be selected independently for each region of the image.
[0044] In one implementation of this embodiment, the encoder uses a fixed- rate region-based compression scheme with a given region size, e.g., 8x8. Each region is compressed independently. If it is not possible to encode every pixel in the region explicitly at the required bit rate, then the region is downscaled by a predetermined ratio prior to compression. For example, the 8x8 region may be reduced in size to 8x6, which would reduce the amount of pixel information that needs to be stored by 25%. The level of information reduction is chosen to allow the region to be encoded at the desired compression acceptability criteria. The downscaling may be accomplished by any appropriate method, with higher quality methods being used to retain more useful information.
[0045] For a given amount of final information, there may be several different ways of scaling the region to reduce the amount of information that needs to be stored by a similar amount. For example, 8x6, 7x7, and 6x8 sets of pixels all require approximately the same amount of final data to encode. For each region, the encoder may try different ratios, and use the ratio that provides the best image quality in terms of the predetermined compression acceptability criteria (selecting from the multiple different quantizations).
[0046] In some regions of the image, it is noted that the method may choose to use a higher level of downscaling (e.g., 8x5, 8x4, 6x5, etc.) and evaluate these ratios in conjunction with the encoder using back-end compression schemes that have a lower compression rate. By reducing the number of unique pixels that need to be stored, the remaining pixels may be encoded with a higher accuracy (i.e., a lower compression rate), while achieving the same predetermined compression acceptability criteria. In smooth regions of an image, it may be advantageous to use these higher levels of downscaling while encoding the final pixels at higher precision. Conversely, in some regions (for example, those regions with more high-frequency content), it may be more optimal in terms of image quality to use minimal or no scaling (quantization), and instead use a higher rate of back-end compression.
[0047] One extension to this embodiment is to downsample information along a selected vector direction, to preserve more of the image quality in the region (rather than the approximation achieved using downsampling aligned to the X and Y axes but with a variable aspect ratio). In this case, the quantization could be the same as above, but the transform is now different. This extension may allow better preservation of detail in regions of the image where the high frequency content is aligned closer to the diagonals. For example, if an image can be downscaled with knowledge of the direction of motion in the image (if any), then the high-frequency information orthogonal to the direction of the motion can be retained, while other information may be discarded.
[0048] A second extension to this embodiment is to subdivide the original region further into subregions, and independently scale each subregion (select a different transform and quantization for each subset) to better match the characteristics of the region to provide a higher image quality.
[0049] Figure 5 is a flow chart of a method 500 for compressing an image that evaluates combinations of regions, subregions, transforms, and quantizers. An image to be encoded is selected (step 502) and the selected image is decomposed into regions (step 504). A region of the image is selected (step 506). To evaluate the selected region of the image, the selected region is split into subregions (step 508), a subregion is selected (step 510), a transform is selected (step 512), and a quantizer is selected (step 514). Based on the selected subregion, transform, and quantizer, the selected subregion of the image is processed and evaluated to determine whether it meets predetermined compression acceptability criteria (step 516). It is noted that the selection of the split (step 508), transform (step 512), and quantizer (step 514) may be performed in any order without affecting the overall operation of the method 500. Optionally, the compression acceptability criteria that are determined by the selected subregion split, transform, and quantizer may be stored for later comparison.
[0050] To ensure that the best possible combination of split, transform, and quantizer are chosen for the selected region, all of the splits, transforms, and quantizers will be evaluated. It should be understood that in an optimized embodiment, the method may not exhaustively enumerate all combinations of region split, subregion split, transform, and quantizer, but may use an optimized search approach to produce the same or similar result.
[0051] If all of the quantizers have not been evaluated or a threshold compression acceptability criteria has not been reached (step 518), then another quantizer is selected (step 514) and processing continues as described above. If all of the quantizers have been evaluated or if the threshold compression acceptability criteria has been reached (step 518), then a determination is made whether all of the transforms have been evaluated or the threshold compression acceptability criteria has been reached (step 520).
[0052] If all of the transforms have not been evaluated or the threshold compression acceptability criteria has not been reached (step 520), then another transform is selected (step 512) and processing continues as described above. If all of the transforms have been evaluated or the threshold compression acceptability criteria has been reached (step 520), then a determination is made whether all subregions have been evaluated (step 522).
[0053] If all of the subregions of the region have not been evaluated (step
522), then another subregion of the region is selected (step 510) and processing continues as described above. If all of the subregions have been evaluated (step 522), then a determination is made whether all of the subregion splits have been evaluated or the threshold compression acceptability criteria has been reached (step 524).
[0054] If all of the subregion splits have not been evaluated and the threshold compression acceptability criteria has not been reached (step 524), then the region is split into different subregions (step 508) and processing continues as described above. In an alternative embodiment (not shown), the threshold compression acceptability criteria defined in steps 518, 520, and 524 may not be used.
[0055] After all combinations of splits, transforms, and quantizers have been evaluated or the threshold compression acceptability criteria for the selected region has been reached, the best splits, transforms, and quantizers are selected (step 526). All of the subregions of the region are encoded using the best subregion splits, transforms, and quantizers (step 528). In one implementation, the encoding in step 528 may also include additional compression. For each region, the output data format includes some metadata to be stored and/or transmitted with the region, to indicate the subregion splits, transforms, and quantizers applied for that region and other information that may be required for decoding.
[0056] Next, a determination is made whether all of the regions of the image have been examined (step 530). If all of the regions of the image have not been examined, then another region of the image is selected (step 506) and processing continues as described above. If all of the regions of the image have been examined (step 530), then the method terminates.
[0057] Other embodiments are possible, where the transformation and quantization are tightly coupled with the final encoding, and also with the implementation of the decoding. In addition to the following two examples, other embodiments are possible.
[0058] In a first example embodiment, texture filtering operations will be performed on the decoded data, so an upscaling filter may be implemented by manipulating the texture filtering hardware, rather than by implementing an additional dedicated upscaler.
[0059] In a second example embodiment, the underlying compression
(encoding) generates index coefficients that are used to select colors. In this case, the transformation and quantization may be performed on the index coefficients produced by the underlying encoder, rather than on the original color data. In this embodiment, the region is compressed prior to the region being transformed and quantized.
[0060] It should be understood that many variations are possible based on the disclosure herein. Although features and elements are described above in particular combinations, each feature or element may be used alone without the other features and elements or in various combinations with or without other features and elements.
[0061] The methods provided may be implemented in a general purpose computer, a processor, or a processor core. Suitable processors include, by way of example, a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), and/or a state machine. Such processors may be manufactured by configuring a manufacturing process using the results of processed hardware description language (HDL) instructions and other intermediary data including netlists (such instructions capable of being stored on a computer readable media). The results of such processing may be maskworks that are then used in a semiconductor manufacturing process to manufacture a processor which implements aspects of the present invention.
[0062] The methods or flow charts provided herein may be implemented in a computer program, software, or firmware incorporated in a non-transitory computer-readable storage medium for execution by a general purpose computer or a processor. Examples of non- transitory computer-readable storage mediums include a read only memory (ROM), a random access memory (RAM), a register, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks, and digital versatile disks (DVDs).
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Claims

CLAIMS What is claimed is:
1. A method for compressing an image, comprising:
decomposing the image into one or more regions;
selecting a region of the image to evaluate;
transforming and quantizing the region if the region does not meet a predetermined compression acceptability criteria;
if the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized:
adjusting the transformation and quantization settings; and transforming and quantizing the region using the adjusted settings; and
encoding the region when the predetermined compression acceptability criteria has been reached.
2. The method according to claim 1, wherein each of the one or more regions has a fixed size and shape.
3. The method according to claim 1, wherein each of the one or more regions has a variable size and shape.
4. The method according to claim 1, wherein the transform and quantization implements a downscaling operation of the region with a selected aspect ratio.
5. The method according to claim 4, further comprising:
compressing each region after downscaling using a fixed or variable bit rate compression scheme.
6. The method according to claim 5, wherein for each region, the compressing includes selecting from a set of available compression methods, with each compression method associated with a set of possible scaling aspect ratios that meet a specific compression acceptability criteria.
7. The method according to claim 1, wherein the encoding includes applying additional levels of compression.
8. The method according to claim 1, wherein the encoding includes storing metadata with the encoded region, the metadata indicating the transformation and quantization applied for the region.
9. A method for compressing an image, comprising:
decomposing the image into one or more regions;
selecting a region of the image to evaluate;
decomposing the selected region into subregions;
transforming and quantizing the subregions if the region does not meet a predetermined compression acceptability criteria;
if the region does not meet the predetermined compression acceptability criteria based on a combination of subregion split, transform, and quantization:
adjusting the subregion split; and
transforming and quantizing the adjusted subregions; and encoding the region when the predetermined compression acceptability criteria has been reached.
10. The method of claim 9, wherein each of the one or more regions has a fixed size and shape.
11. The method of claim 9, wherein each of the one or more regions has a variable size and shape.
12. The method of claim 9, wherein the transform and quantization implements a downscaling operation of the region with a selected aspect ratio.
13. The method according to claim 12, further comprising:
compressing each region after downscaling using a fixed or variable bit rate compression scheme.
14. The method according to claim 13, wherein for each region, the compressing includes selecting from a set of available compression methods, with each compression method associated with a set of possible scaling aspect ratios that meet a specific compression acceptability criteria.
15. The method according to claim 9, wherein the encoding includes applying additional levels of compression.
16. The method according to claim 9, wherein the encoding includes storing metadata with the encoded region, the metadata indicating the transform and quantization applied for the region.
17. A method for decompressing an image, the image including one or more regions, the method comprising:
selecting a region of the image to decode;
decoding the selected region and metadata associated with the selected region; and
applying a reconstruction transformation to the selected region, wherein the metadata includes information regarding the reconstruction transformation.
18. The method according to claim 17, wherein the reconstruction transformation includes using an upscaling filter.
19. The method according to claim 18, wherein a type of upscaling filter is uniform over the entire image or is selected independently for each region of the image.
20. A method for decompressing an image, the image including one or more regions, each of which includes one or more subregions, the method comprising:
selecting a region of the image to decompress;
decoding the selected region and metadata associated with the selected region; and
applying reconstruction transformations to each of the subregions in the selected region, wherein the metadata includes information regarding the reconstruction transformations.
21. The method according to claim 20, wherein the reconstruction transformation includes using an upscaling filter.
22. The method according to claim 20, wherein a type of upscaling filter is uniform over the entire image or is selected independently for each region of the image.
23. A system for compressing an image, comprising:
an encoder configured to:
decompose the image into one or more regions;
select a region of the image to evaluate;
transform and quantize the region if the region does not meet a predetermined compression acceptability criteria;
if the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized:
adjust the transformation and quantization settings; and transform and quantize the region using the adjusted settings; and
encode the region when the predetermined compression acceptability criteria has been reached.
24. The system according to claim 23, wherein the encoder is further configured to decompose the image into one or more regions having a fixed size and shape.
25. The system according to claim 23, wherein the encoder is further configured to decompose the image into one or more regions having a variable size and shape.
26. The system according to claim 23, wherein the encoder is further configured to implement the transform and quantization by performing a downscaling operation of the region with a selected aspect ratio.
27. The system according to claim 26, wherein the encoder is further configured to:
compress each region after downscaling using a fixed or variable bit rate compression scheme.
28. The system according to claim 27, wherein for each region, the encoder is further configured to select from a set of available compression methods, with each compression method associated with a set of possible scaling aspect ratios that meet a specific compression acceptability criteria.
29. The system according to claim 23, wherein the encoder is further configured to apply additional levels of compression.
30. The system according to claim 23, wherein the encoder is further configured to store metadata with the encoded region, the metadata indicating the transformation and quantization applied for the region.
31. A system for decompressing an image, the image including one or more regions, the system comprising: a decoder configured to:
select a region of the image to decode;
decode the selected region and metadata associated with the selected region; and
apply a reconstruction transformation to the selected region, wherein the metadata includes information regarding the reconstruction transformation.
32. The system according to claim 31, wherein the reconstruction transformation includes using an upscaling filter.
33. The system according to claim 31, wherein a type of upscaling filter is uniform over the entire image or is selected independently for each region of the image.
34. A non- transitory computer-readable storage medium storing a set of instructions for execution by a general purpose computer to compress an image, the set of instructions comprising:
a decomposing code segment for decomposing the image into one or more regions;
a selecting code segment for selecting a region of the image to evaluate; a transforming and quantizing code segment for transforming and quantizing the region if the region does not meet a predetermined compression acceptability criteria;
an adjusting code segment for adjusting the transformation and quantization settings if the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized; and an encoding code segment for encoding the region when the predetermined compression acceptability criteria has been reached.
35. The non-transitory computer-readable storage medium according to claim 34, wherein the instructions are hardware description language (HDL) instructions used for the manufacture of a device.
36. A method for compressing an image, comprising:
decomposing the image into one or more regions;
selecting a region;
splitting the selected region into one or more subregions;
selecting a subregion;
selecting one of a plurality of transforms;
selecting one of a plurality of quantizers;
evaluating the selected subregion split, transform, and quantizer against a predetermined compression acceptability criteria;
iteratively selecting each of the subregions, the subregion splits, the transforms, and the quantizers to determine a best subregion split, transform, and quantizer in terms of the predetermined compression acceptability criteria; and
encoding all of the subregions using the best subregion split, transform, and quantizer when the predetermined compression acceptability criteria has been reached.
37. The method according to claim 36, wherein:
the iteratively selecting terminates early if a threshold compression acceptability criteria is met; and
the subregion split, transform, and quantizer that were selected when the threshold compression acceptability criteria is met are used to encode all of the subregions.
38. A method for compressing an image, comprising:
decomposing the image into one or more regions;
selecting a region of the image to evaluate; compressing the selected region;
transforming and quantizing the compressed region if the compressed region does not meet a predetermined compression acceptability criteria;
if the transformed and quantized region does not meet the predetermined compression acceptability criteria after it has been transformed and quantized:
adjusting the transformation and quantization settings; and transforming and quantizing the compressed region using the adjusted settings; and
encoding the transformed and quantized region when the predetermined compression acceptability criteria has been reached.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3258689A4 (en) * 2015-03-02 2018-01-31 Samsung Electronics Co., Ltd. Method and device for compressing image on basis of photography information
US12126816B2 (en) 2023-02-24 2024-10-22 BAE Systems Imaging Solutions Inc. Techniques for image data compression automation

Families Citing this family (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2014532377A (en) * 2011-10-14 2014-12-04 アドバンスト・マイクロ・ディバイシズ・インコーポレイテッドＡｄｖａｎｃｅｄ Ｍｉｃｒｏ Ｄｅｖｉｃｅｓ Ｉｎｃｏｒｐｏｒａｔｅｄ Region-based image compression
GB201414204D0 (en) * 2014-08-11 2014-09-24 Advanced Risc Mach Ltd Data processing systems
JP6847033B2 (en) 2014-10-10 2021-03-24 アドバンスト・マイクロ・ディバイシズ・インコーポレイテッドＡｄｖａｎｃｅｄ Ｍｉｃｒｏ Ｄｅｖｉｃｅｓ Ｉｎｃｏｒｐｏｒａｔｅｄ Hybrid block-based compression
EP3306922A1 (en) * 2016-10-05 2018-04-11 Thomson Licensing Method and apparatus for encoding a picture using rate-distortion based block splitting
WO2018179851A1 (en) * 2017-03-28 2018-10-04 Sharp Kabushiki Kaisha Systems and methods for determining a level of quantization
US10869040B2 (en) * 2017-10-29 2020-12-15 Chun-Wei Chan Perceptual multimedia encoding system and method with pre-defined encoding quality patterns
WO2019125191A1 (en) 2017-12-18 2019-06-27 Motorola Solutions, Inc Method and device for generating an augmented image
JP7109961B2 (en) * 2018-03-29 2022-08-01 Kddi株式会社 Image decoding device, image encoding device, image processing system, image decoding method and program
WO2019235946A1 (en) 2018-06-07 2019-12-12 Motorola Solutions, Inc System and method for sending and rendering an image by a device based on receiver's context
JP2020150516A (en) * 2019-03-15 2020-09-17 シャープ株式会社 Image decoding device and image encoding device
US11106039B2 (en) * 2019-08-26 2021-08-31 Ati Technologies Ulc Single-stream foveal display transport
KR20210078218A (en) * 2019-12-18 2021-06-28 삼성전자주식회사 Electronic apparatus and method of controlling the same
CN112906721B (en) * 2021-05-07 2021-07-23 腾讯科技（深圳）有限公司 Image processing method, device, equipment and computer readable storage medium

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0785688A2 (en) * 1995-12-27 1997-07-23 Sony Corporation Hierarichal encoding of videosignals
US20070189621A1 (en) * 2006-02-15 2007-08-16 Aten International Co., Ltd Image transmission system
WO2008027413A2 (en) * 2006-08-31 2008-03-06 Ati Technologies Inc. Texture compression techniques

Family Cites Families (73)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0284895A (en) * 1988-09-20 1990-03-26 Nippon Telegr & Teleph Corp <Ntt> Picture encoding system
US5144423A (en) * 1990-12-11 1992-09-01 At&T Bell Laboratories Hdtv encoder with forward estimation and constant rate motion vectors
WO1994022108A1 (en) * 1993-03-23 1994-09-29 Zoran Corporation Rapid thumbnail image reconstruction of dct compressed image data
JP3526316B2 (en) * 1993-10-21 2004-05-10 三洋電機株式会社 Video compression encoding method
US5604824A (en) * 1994-09-22 1997-02-18 Houston Advanced Research Center Method and apparatus for compression and decompression of documents and the like using splines and spline-wavelets
JPH08205140A (en) * 1995-01-31 1996-08-09 Canon Inc Image compressing device
KR100355375B1 (en) 1995-11-01 2002-12-26 삼성전자 주식회사 Method and circuit for deciding quantizing interval in video encoder
JPH10174103A (en) * 1996-12-13 1998-06-26 Matsushita Electric Ind Co Ltd Image encoder, encoded image recording medium, image decoder, image encoding method and encoded image transmitting method
US5956431A (en) * 1997-10-02 1999-09-21 S3 Incorporated System and method for fixed-rate block-based image compression with inferred pixel values
US6185253B1 (en) * 1997-10-31 2001-02-06 Lucent Technology, Inc. Perceptual compression and robust bit-rate control system
EP0955609B1 (en) * 1998-05-07 2003-07-30 Sarnoff Corporation Decoding compressed image information
AU768853B2 (en) * 1998-05-14 2004-01-08 Interval Research Corporation Video compression with storage reduction, color rotation, combined signal and border filtering
US6396958B1 (en) * 1998-09-25 2002-05-28 Lockheed Martin Corporation Image transmission system and method employing compression and error correction
JP2002536895A (en) 1999-02-04 2002-10-29 クビス・インク Quality priority image preservation and communication
EP1158811A4 (en) * 1999-03-05 2002-01-09 Toshiba Kk Method and apparatus for coding moving picture image
AUPR222500A0 (en) * 2000-12-21 2001-01-25 Unisearch Limited Method for efficient scalable compression of video
US6606418B2 (en) * 2001-01-16 2003-08-12 International Business Machines Corporation Enhanced compression of documents
US7062445B2 (en) * 2001-01-26 2006-06-13 Microsoft Corporation Quantization loop with heuristic approach
US20030021486A1 (en) * 2001-07-27 2003-01-30 Tinku Acharya Method and apparatus for image scaling
US6856701B2 (en) * 2001-09-14 2005-02-15 Nokia Corporation Method and system for context-based adaptive binary arithmetic coding
US7076108B2 (en) * 2001-12-11 2006-07-11 Gen Dow Huang Apparatus and method for image/video compression using discrete wavelet transform
US7206448B2 (en) * 2002-02-28 2007-04-17 At&T Corp. System and method for using pattern vectors for video and image coding and decoding
RU2322770C2 (en) * 2002-04-23 2008-04-20 Нокиа Корпорейшн Method and device for indication of quantizer parameters in video encoding system
JP3988990B2 (en) * 2002-08-27 2007-10-10 株式会社リコー Code conversion apparatus, code conversion method, program, and recording medium
AU2003279015A1 (en) * 2002-09-27 2004-04-19 Videosoft, Inc. Real-time video coding/decoding
CN101409835B (en) * 2002-11-08 2014-09-17 苹果公司 Method and apparatus for controlling rate-distortion tradeoff using lagrange multiplier and visual masking
KR20060109247A (en) * 2005-04-13 2006-10-19 엘지전자 주식회사 Method and apparatus for encoding/decoding a video signal using pictures of base layer
JP4250458B2 (en) * 2003-05-30 2009-04-08 キヤノン株式会社 Image display method and image processing apparatus for image system
US7830963B2 (en) * 2003-07-18 2010-11-09 Microsoft Corporation Decoding jointly coded transform type and subblock pattern information
US7782940B2 (en) * 2003-08-01 2010-08-24 Polycom, Inc. Methods for encoding or decoding in a videoconference system to reduce problems associated with noisy image acquisition
US20050063562A1 (en) * 2003-08-07 2005-03-24 Brunk Hugh L. Conveying fingerprint minutiae with digital watermarks
US7362804B2 (en) * 2003-11-24 2008-04-22 Lsi Logic Corporation Graphical symbols for H.264 bitstream syntax elements
US7986731B2 (en) * 2004-02-06 2011-07-26 Apple Inc. H.264/AVC coder incorporating rate and quality controller
TW200618610A (en) * 2004-07-20 2006-06-01 Qualcomm Inc Method and apparatus for motion vector processing
KR100696451B1 (en) * 2005-10-20 2007-03-19 재단법인서울대학교산학협력재단 Method and apparatus for video frame recompression combining down-sampling and max-min quantizing mode
KR101334173B1 (en) * 2006-01-11 2013-11-28 삼성전자주식회사 Method and apparatus for encoding/decoding graphic data
US20070242749A1 (en) * 2006-04-14 2007-10-18 Sung Chih-Ta S Image frame compression of video stream with fast random accessing and decompressing
US8582663B2 (en) * 2006-08-08 2013-11-12 Core Wireless Licensing S.A.R.L. Method, device, and system for multiplexing of video streams
WO2008021240A2 (en) * 2006-08-10 2008-02-21 Fastvdo, Llc A method and compact apparatus for video capture and transmission with a common interface
US8250618B2 (en) * 2006-09-18 2012-08-21 Elemental Technologies, Inc. Real-time network adaptive digital video encoding/decoding
WO2008054100A1 (en) * 2006-11-01 2008-05-08 Electronics And Telecommunications Research Institute Method and apparatus for decoding metadata used for playing stereoscopic contents
KR101362941B1 (en) * 2006-11-01 2014-02-17 한국전자통신연구원 Method and Apparatus for decoding metadata used for playing stereoscopic contents
CN100556144C (en) * 2007-02-14 2009-10-28 浙江大学 Be used for method and the code device of avoiding video or image compression inverse transformation to cross the border
US8582647B2 (en) 2007-04-23 2013-11-12 Qualcomm Incorporated Methods and systems for quality controlled encoding
CN100562118C (en) * 2007-07-03 2009-11-18 上海富瀚微电子有限公司 Code rate control method for video coding
US20090016624A1 (en) * 2007-07-12 2009-01-15 Chih-Ta Star Sung Method of graphics and image data compression
CA2604317C (en) * 2007-08-06 2017-02-28 Historx, Inc. Methods and system for validating sample images for quantitative immunoassays
JP2009177531A (en) * 2008-01-24 2009-08-06 Panasonic Corp Image recording device, image reproducing device, recording medium, image recording method, and program
KR101448308B1 (en) * 2008-02-04 2014-10-08 삼성전자주식회사 Method and apparatus for generating thumbnail image
US9003280B2 (en) * 2008-05-09 2015-04-07 Vizio, Inc. Displaying still and moving images of a constant size or images that occupy a specified percentage of a screen across different size display screens
US8243117B2 (en) * 2008-09-26 2012-08-14 Microsoft Corporation Processing aspects of a video scene
US8805106B2 (en) * 2008-09-26 2014-08-12 Futurewei Technologies, Inc. System and method for compressing and decompressing images and video
JP4878051B2 (en) * 2008-12-04 2012-02-15 日本電信電話株式会社 Encoded stream transmission method, encoded stream transmission apparatus, encoded stream transmission control program, and recording medium therefor
US20100226441A1 (en) * 2009-03-06 2010-09-09 Microsoft Corporation Frame Capture, Encoding, and Transmission Management
CN105791861B (en) * 2009-04-20 2018-12-04 杜比实验室特许公司 Orient interpolation and Data Post
US8724707B2 (en) * 2009-05-07 2014-05-13 Qualcomm Incorporated Video decoding using temporally constrained spatial dependency
KR101676311B1 (en) * 2009-10-13 2016-11-15 엘지전자 주식회사 Broadcast receiver and 3d video data processing method thereof
CN102656884A (en) * 2009-12-16 2012-09-05 国际商业机器公司 Video coding using pixel-streams
WO2011087963A1 (en) * 2010-01-15 2011-07-21 Dolby Laboratories Licensing Corporation Edge enhancement for temporal scaling with metadata
EP2526698A1 (en) * 2010-01-22 2012-11-28 Thomson Licensing Methods and apparatus for sampling -based super resolution video encoding and decoding
TR201001101A2 (en) * 2010-02-12 2011-09-21 Vestel Elektroni̇k Sanayi̇ Ve Ti̇caret A.Ş. A data compression method.
SG184528A1 (en) * 2010-04-09 2012-11-29 Mitsubishi Electric Corp Moving image encoding device and moving image decoding device
CN101854555B (en) * 2010-06-18 2011-07-27 上海交通大学 Video coding system based on prediction residual self-adaptation regulation
US8780972B2 (en) * 2011-02-25 2014-07-15 Blackberry Limited Methods and devices for data compression using offset-based adaptive reconstruction levels
CN107454410B (en) * 2011-04-22 2020-03-20 杜比国际公司 Lossy compression coding data method and device and corresponding data reconstruction method and device
JP2012235383A (en) * 2011-05-06 2012-11-29 Sony Corp Encoder, decoder, encoder system, decoder system, transmission adapter, encoding method, decoding method, and imaging apparatus
WO2013036972A1 (en) * 2011-09-09 2013-03-14 Panamorph, Inc. Image processing system and method
US20130083845A1 (en) * 2011-09-30 2013-04-04 Research In Motion Limited Methods and devices for data compression using a non-uniform reconstruction space
JP2014532377A (en) * 2011-10-14 2014-12-04 アドバンスト・マイクロ・ディバイシズ・インコーポレイテッドＡｄｖａｎｃｅｄ Ｍｉｃｒｏ Ｄｅｖｉｃｅｓ Ｉｎｃｏｒｐｏｒａｔｅｄ Region-based image compression
US9326491B1 (en) * 2011-12-08 2016-05-03 Harry E. Hegarty Fluid misting deterrent system for bicycles
US20140177706A1 (en) * 2012-12-21 2014-06-26 Samsung Electronics Co., Ltd Method and system for providing super-resolution of quantized images and video
US20150133214A1 (en) * 2013-11-11 2015-05-14 Amazon Technologies, Inc. Video encoding based on areas of interest
US9774865B2 (en) * 2013-12-16 2017-09-26 Samsung Electronics Co., Ltd. Method for real-time implementation of super resolution

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0785688A2 (en) * 1995-12-27 1997-07-23 Sony Corporation Hierarichal encoding of videosignals
US20070189621A1 (en) * 2006-02-15 2007-08-16 Aten International Co., Ltd Image transmission system
WO2008027413A2 (en) * 2006-08-31 2008-03-06 Ati Technologies Inc. Texture compression techniques

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
KIM I K ET AL: "Rate-distortion optimization of the image compression algorithm based on the warped discrete cosine transform", SIGNAL PROCESSING, ELSEVIER SCIENCE PUBLISHERS B.V. AMSTERDAM, NL, vol. 83, no. 9, 1 September 2003 (2003-09-01), pages 1919 - 1928, XP004443668, ISSN: 0165-1684, DOI: 10.1016/S0165-1684(03)00110-5 *
WOO-JIN HAN ET AL: "Improved Video Compression Efficiency Through Flexible Unit Representation and Corresponding Extension of Coding Tools", IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, IEEE SERVICE CENTER, PISCATAWAY, NJ, US, vol. 20, no. 12, 1 December 2010 (2010-12-01), pages 1709 - 1720, XP011329409, ISSN: 1051-8215, DOI: 10.1109/TCSVT.2010.2092612 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3258689A4 (en) * 2015-03-02 2018-01-31 Samsung Electronics Co., Ltd. Method and device for compressing image on basis of photography information
US10735724B2 (en) 2015-03-02 2020-08-04 Samsung Electronics Co., Ltd Method and device for compressing image on basis of photography information
US12126816B2 (en) 2023-02-24 2024-10-22 BAE Systems Imaging Solutions Inc. Techniques for image data compression automation

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