Image analysis – Image compression or coding – Pyramid – hierarchy – or tree structure
Reexamination Certificate
1997-12-31
2002-06-18
Mancuso, Joseph (Department: 2623)
Image analysis
Image compression or coding
Pyramid, hierarchy, or tree structure
C382S239000
Reexamination Certificate
active
06408101
ABSTRACT:
The invention relates generally to a system for encoding image sequences and, more particularly, to apparatus and a concomitant method for reducing the computational complexity in determining motion vectors for block-based motion estimation and for enhancing the accuracy of motion estimates.
BACKGROUND OF THE INVENTION
An image sequence, such as a video image sequence, typically includes a sequence of image frames or pictures. The reproduction of video containing moving objects typically requires a frame speed of thirty image frames per second, with each frame possibly containing in excess of a megabyte of information. Consequently, transmitting or storing such image sequences requires a large amount of either transmission bandwidth or storage capacity. To reduce the necessary transmission bandwidth or storage capacity, the frame sequence is compressed such that redundant information within the sequence is not stored or transmitted. Television, video conferencing and CD-ROM archiving are examples of applications which can benefit from efficient video sequence encoding.
Generally, to encode an image sequence, information concerning the motion of objects in a scene from one frame to the next plays an important role in the encoding process. Because of the high redundancy that exists between consecutive frames within most image sequences, substantial data compression can be achieved using a technique known as motion estimation/compensation. In brief, the encoder only encodes the differences relative to areas that are shifted with respect to the areas coded. Namely, motion estimation is a process of determining the direction and magnitude of motion (motion vectors) for an area (e.g., a block or macroblock) in the current frame relative to one or more reference frames. Whereas, motion compensation is a process of using the motion vectors to generate a prediction (predicted image) of the current frame. The difference between the current frame and the predicted frame results in a residual signal (error signal), which contains substantially less information than the current frame itself. Thus, a significant saving in coding bits is realized by encoding and transmitting only the residual signal and the corresponding motion vectors.
To illustrate, in a sequence containing motion, a current frame can be reconstructed using an immediately preceding frame and the residual signal representing the difference between the current and the immediately preceding frame. The transmitter or encoder transmits the preceding frame, the residual signal and the corresponding motion vectors to a receiver. At the receiver, the current frame is reconstructed by combining the preceding frame with the residual signal and the motion information. Consequently, only one (1) frame and the difference information with its associated motion vectors are transmitted and received rather than two (2) entire frames.
However, encoder designers must address the dichotomy of attempting to increase the precision of the motion estimation process to minimize the residual signal (i.e., reducing coding bits) or accepting a lower level of precision in the motion estimation process to minimize the computational overhead. Namely, determining the motion vectors from the frame sequence requires intensive searching between frames to determine the motion information. A more intensive search will generate a more precise set of motion vectors at the expense of more computational cycles.
For examples, many systems determine motion information using a so-called block based approach. In a simple block based approach, the current frame is divided into a number of blocks of pixels (referred to hereinafter as the current blocks). For each of these current blocks, a search is performed within a selected search area in the preceding frame for a block of pixels that “best” matches the current block. This search is typically accomplished by repetitively comparing a selected current block to similarly sized blocks of pixels in the selected search area of the preceding frame. Once a block match is found, the location of matching block in the search area in the previous frame relative to the location of the current block within the current frame defines a motion vector. This approach, i.e., comparing each current block to an entire selected search area, is known as a full search approach or the exhaustive search approach. The determination of motion vectors by the exhaustive search approach is computationally intensive, especially where the search area is particularly large. A such, these systems tend to be relatively slow in processing the frames and expensive to fabricate.
Therefore, there is a need in the art for an apparatus and a concomitant method for reducing the computational complexity in determining motion vectors for block-based motion estimation.
SUMMARY OF THE INVENTION
The present invention is an apparatus and method for reducing the computational complexity in determining motion vectors for block-based motion estimation and for enhancing the accuracy of motion estimation methods. More specifically, the present invention decomposes each of the image frames within an image sequence into a M-ary pyramid. The blocks within the image frame are then classified into blocks of high activity versus blocks of low activity. This classification rapidly provides useful “feature” information to the motion estimation method which then applies this feature information to further enhance the motion estimation process.
REFERENCES:
patent: 5799111 (1998-08-01), Guissin
patent: 6236758 (2001-05-01), Sodagar et al.
“A Fast Hierarchical Motion Vector Estimation Algorithm Using Mean Pyramid”, Nam et al., IEEE Transactions on Circuits and Systems for Video Technology, vol. 5, No. 4, Aug. 1995, pp. 344-351.
“A Fast Hierarchical Motion-Compensation Scheme for Video Coding Using Block Feature Matching”, X. Lee and Y-Q. Zhang, IEEE Trans. on Circuits and Systems for Video Technology, vol. 6, No. 6, Dec. 1996, pp. 627-635.
“Block Motion Vector Estimation Using Edge Matching: An Approach with Better Frame Quality as Compared to Full Search Algorithm” Y-L. Chan, W-C. Siu, 1997 IEEE Int. Symp. on Circuits and Syst., Jun. 9-12, 1997, Hong Kong.
“Low-Complexity Block-Based Motion Estimation via One-Bit Transforms”, Natarajan et al., IEEE Transactions on Circuits and Systems for Video Technology, vol. 7, No. 4, Aug. 1997, pp. 702-706.
Chiang Tihao
Krishnamurthy Ravi
Song Zudong
Zhang Ya-Qin
Bali Vikkram
Burke William J.
Mancuso Joseph
Sarnoff Corporation
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