Image analysis – Image compression or coding
Reexamination Certificate
1999-10-29
2003-03-18
Johns, Andrew W. (Department: 2621)
Image analysis
Image compression or coding
C382S233000, C382S266000
Reexamination Certificate
active
06535643
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to an image processing technique, and in particular to a method for recovering a compressed video signal and an apparatus therefor.
2. Description of the Prior Art
The image compression technique of MPEG, MPEG2, H261, H263, etc. is implemented by a Hybrid MC DCT (Motion Compensation Discrete Cosine Transform) technique. This hybrid MC DCT is classified into an encoding process and decoding processes. In the encoding process, the original image is divided into a plurality of blocks for compressing the information of a spacious region, and a two-dimensional DCT is performed with respect to each block, and a redundancy is decreased in the image or between the images using a correlation on a time axis between the images for decreasing the information of the time region. In addition, in the decoding process, the reverse sequence of the decoding process is performed. In order to implement the MCDCT technique, an encoder and decoder are required.
FIG. 1
is a block diagram illustrating a conventional image encoder. As shown therein, an input video signal is subtracted by a subtractor
1
with a motion compensated video signal from a video memory
9
and is inputted via a first switching unit
2
and a DCT unit
3
. The DCT unit
3
processes the inputted video signal based on a DCT, and a quantization unit
4
quantizes a DCT-processed video signal and outputs a DCT coefficient q. This coefficient is reversely quantized by a reverse quantizing unit
6
and is processed based on a reverse DCT by a reverse DCT unit
7
for thereby recovering the original video signal. The thusly recovered video signal is summed by a summing unit
8
with a video signal recovered in the earlier process via a second switching unit
10
and is inputted into the video memory. A controller
5
controls the first and second switching units
2
and
10
and transmits an intra/inter information (p=mtype; flag for INTRA/INTER), a transmission information (q; flag for transmitted or not), and an quantizing information (qz=Qp; quantizer indication) to a decoder (not shown in FIG.
1
). The video memory
9
outputs a motion vector information (v=MV; motion vector) to the decoder. The DCT unit
3
outputs a DCT coefficient q to the decoder.
While the video signal is being coded, the information may be lost during the quantizing process. Therefore, the video signals reconstructed by the decoder may cause blocking artifacts and ring effects. The block artifacts occur when quantizing a low frequency DCT coefficient, and the ring effects occur due to the information loss of the original video in the quantizing process for a high frequency DCT coefficient.
Namely, in the case of the coding technique using a DCT in a system which is capable of coding a still picture or a motion picture, the entire image is divided into a plurality of small images (for example, 8×8 blocks), and then a transforming operation is performed with respect to the divided blocks, and the original image is processed based on a DCT, and an important information of the original image based on a result of the conversion is included in the low frequency component. As the component becomes high frequency, the important information is decreased. The low frequency component includes an information related to the neighboring block. The DCT transform is performed without considering a correlation between the blocks. Namely, the low frequency components are quantized by the blocks, so that a continuity between the neighboring blocks is lost. This phenomenon is called as the blocking artifacts.
In addition, when quantizing the coefficients obtained when performing the DCT operation, as the interval of the quantizing operation is increased, the components to be coded is decreased. Therefore, the number of bits which will be processed is decreased, so that a distortion occurs in the reconstructed original image. This phenomenon is called as the ring effects. The ring effects which occur when increasing the intervals of the quantizing operations are increased at a contour line of an object among the images.
As a technique for removing the above-described block artifacts and ring effects, a low pass filter technique and a regularization recovering technique are generally used.
The low pass filter sets a filter tap or a filter coefficient based on or by selecting (filter mask) a plurality of pixels near a certain pixel and obtaining an average of the pixels. The recovered images are over smoothed in accordance with the kinds of images, and a compression ratio.
In the regularization recovering method, the block artifacts are adaptively processed in accordance with the statistical characteristic of the images. Namely, a non-uniform information is all computed at all direction boundary areas and in the interior of the block. However, since the computed values have a matrix form, it is impossible to implement a real time computation due to a large amount of computation. In addition, with an exception for the amount of non-uniformity, since an average is comprehensively adapted based on a result of the computation of the non-uniform information, in the block having a large amount of non-uniformity, the degree of the non-uniformity is decreased. On the contrary, the degree of the non-uniformity may be increased. Therefore, it is hard to say it is well adaptive to the system.
The above-described two techniques have advantages and disadvantages in view of a complexity and performance increase of the system. Namely, the low pass filter technique has less computation amount compared to the regularization recovering technique and has a small capacity for adaptively processing the images, so that the information is lost at an edge portion. The regularization recovering method has an excellent performance and requires a large amount of computation when computing regularization parameters.
SUMMARY OF THE INVENTION
Accordingly, in the present invention, it is possible to removing a block artifact and ring effect which occur in a decoded video signal.
In addition, it is possible to define a cost function having a directional feature by the unit of pixels during a decoding operation and obtain a regularization parameter based on the cost function.
To achieve the above objects, there is provided a method for recovering a compressed motion picture according to an embodiment of the invention, comprising the steps of defining a cost function having a smoothing degree of an image and a reliability with respect to an original image in consideration of the directional characteristics of the pixels which will be recovered and a plurality of pixels near the recovering pixels, obtaining a regularization parameter variable having a weight value of a reliability with respect to an original image based on the cost function, and approximating the regularization parameter variable using the compressed pixel and obtaining a recovering pixel.
These and other objects of the present application will become more readily apparent from the detailed description given hereinafter. However, it should be understood that the detailed description and specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.
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“Iterative Projection Algorithms For Removing The Blocking Artifacts Of Bock-DCT Compressed Images ”, Yang et al., IEEE 1993, pp. V405-V408.*
“Iterative Procedures for Reduction of Blocking Effects in Transform Image Coding”, Zakhor, IEEE Transactions on Circuits and S
Birch & Stewart Kolasch & Birch, LLP
LG Electronics Inc.
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