Systems and methods for post-processing decompressed images

Details Systems and methods for post-processing decompressed images Systems and methods for post-processing decompressed images

1998-12-03

2001-11-13

Lee, Thomas D. (Department: 2724)

Image analysis

Image enhancement or restoration

Edge or contour enhancement

C382S275000

Reexamination Certificate

active

06317522

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to systems and methods for post-processing decompressed images in order to minimize perceptual artifacts due to prior image compression, and in particular to such prior image compression methods that process images as independent blocks of pixels.
2. Description of the Related Art
Many important image compression methods process images as independent blocks of pixels. For example, such families of compression standards as JPEG, MPEG, H.320, and so forth, specify a step involving discrete cosine transformation (“DCT”) of independent, non-overlapping 8×8 blocks of pixels in the source image followed by quantization of the resulting transform coefficients. See, e.g., Jack, 1996
, Video Demystified
, HighText Interactive Inc., San Diego, Calif. The quantized transform coefficients are transmitted from a transmitter-encoder to a receiver-decoder. Such transformation and quantization together achieve compression by exploiting the significant correlations that typically occur between the values of pixels in 8×8 blocks, but result in loss of image information (“lossy” compression), the coarser the quantization the greater the loss.
Decompressing images so compressed, which necessarily involves steps of dequantization and inverse DCT of the received quantized coefficients in order to derive a received decompressed image, can lead to what are called herein “blocking artifacts” in the following manner. In certain areas of a received image, the quantization errors introduced can become especially apparent and even objectionable. Especially, in regions where the image is fairly smooth, with little high spatial frequencies components, errors in the low spatial frequency components can make the individual, independent 8×8 blocks perceptually apparent. This is especially so if low frequency components, which smoothed the block-to-block boundaries in the source image, are set to zero.
Several methods of reducing such blocking artifacts are available in the current state of the art. Simple lowpass filtering applied to the decompressed image can blur blocking artifacts and reduce their prominence to some extent, but it necessarily leads also to an overall degraded sharpness in the image. Blocks can be overlapped in the source image in order to redundantly encode block-to-block boundaries, but at the cost of decreased compression and increased required communication bandwidth.
Further, Pennebaker et al., 1993
, JPEG Still Image Compression
, Van Nostrand Reinhard, chap. 16, discloses JPEG block smoothing by fitting quadratic surfaces to the average values of pixels (equivalent to the “DC”, or lowest order, transform coefficient) in adjacent blocks, a computationally complex process. Lakhani, 1996, “Improved Image Reproduction from DC Components”, Opt. Eng. 35:3449-2452, discloses equations for predicting low frequency transform coefficients from DC coefficients that are improved from those in the JPEG standard. Finally, Jeon et al., 1995, Blocking Artifacts Reduction in Image Coding Based on Minimum Block Boundary Discontinuity, Proc SPIE 2501:189-209, discloses a complex and computationally expensive iterative method for zeroing block boundary discontinuities.
Importantly, all current art methods appear to achieve blocking artifact reduction by in one fashion or another performing versions of spatial low-pass filtering. These current art methods also all suffer from one or more additional problems, such as producing overall image degradation, limiting image compression, failing to explicitly address the perceptual aspects of blocking artifacts, requiring excessive computational resources, and so forth.
What is needed, therefore, is a method and system for post-processing decompressed images which is computationally efficient, avoids spatial low-pass filtering, does not produce image degradation, has no effect on compression, and, most importantly, minimizes the perceptual aspects of blocking artifacts.
Citation of a reference herein, or throughout this specification, is not to construed as an admission that such reference is prior art to the Applicant's invention of the invention subsequently claimed.
SUMMARY OF THE INVENTION
The objects of the present invention are to provide systems and methods for post-processing decompressed images in order to minimize blocking artifacts and which overcome the above identified problems in the current art.
Fundamentally, these objects are achieved by methods which achieve blocking artifact reduction by correcting the surface defined by the pixel values in a block of pixels with “bending”, “tilting”, or “twisting” deformations in order to more closely match pixel-value surfaces of adjoining pixel blocks. Since low-pass filtering is avoided by such surface deformations, the corrections added to the pixel values by the methods of this invention more closely match the actual errors and artifacts introduced by the image blocking process.
In detail, these objects are achieved by determining an 8×8 matrix of correction values for each processed 8×8 pixel block in an image. The correction matrices are then added to the pixel blocks in order to derive post-processed pixel blocks with minimized blocking artifacts. The resulting pixel values of the corrected pixel blocks blend with pixel values of adjacent blocks, also typically corrected, in a perceptually smooth manner with minimum block-to-block artifacts. The correction matrices are derived from differences between values of pixels along the edges of a block to be post-processed and pixels along the edges of the four orthogonally adjacent pixel blocks. Alternatively, the correction matrix is derived from zero-frequency (“DC”) transform coefficients of a pixel block to be post-processed and the four adjacent pixel blocks.
The 8×8 matrix of correction values is either derived directly according to a preferred entirely spatial-domain interpolation, or derived indirectly by an alternative computation from a smaller 4×4 spatial-domain intermediary error correction matrix. Direct and inverse transforms of the intermediary correction matrix to and back from a frequency domain accomplish smooth interpolation of the smaller intermediary matrix to an 8×8 matrix of correction values. Preferably, decoded blocks are selected for post-processing principally in relatively flat or featureless image regions. Such image regions are most likely to have perceptually apparent blocking artifacts.
In detail, these objects are achieved by the following embodiments of this invention. In a first embodiment, the present invention includes a method for post-processing a decompressed image, the image having been compressed by a process including independent compression of non-overlapping rectangular blocks of pixels covering the original image, the method comprising: determining four or more quantities for each pixel block in the decompressed image that are representative of blocking artifacts, wherein the four or more quantities for a pixel block are determined from block-to-block differences between combinations of values of pixels in that pixel block and combinations of values of pixels in the four pixel blocks orthogonally adjacent to that pixel block, selecting pixel blocks for post-processing according to the four or more quantities for each pixel block and a threshold value, determining an error correction matrix for each selected pixel block from the four or more quantities for that selected pixel block, wherein the error correction matrices have the same size as the pixel blocks, and adding the error correction matrices to the selected pixel blocks to derive post-processed pixel blocks and the post-processed image.
In a first aspect of the first embodiment, the four or more quantities for a pixel block are four quantities determined from the four differences between averages of values of pixels along each edge of that pixel block and averages of values of pixels along adjacent edges of the adjacent p

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