STEREO MATCHING ALGORITHM-BASED ON MODIFIED WAVELET DECOMPOSITION PROCESS

Multiresolutional representation such as pyramidal structures is usefu l for stereo matching as coarse-to-fine strategy. However, conventiona l pyramidal structures using Gaussian or Laplacian filters lose much i nformation due to their low-pass filtering characteristics and also ca nnot obtain any spatial orientation selectivity. The adoption of wavel et transform can remedy these problems, but at the time of image trans lation, it changes wavelet coefficients. In this paper, a pyramid usin g modified wavelet decomposition process is proposed to have translati on invariance. The image transformed by the proposed method is convert ed into appropriate multiple features without loss of information. Sin ce the importance of each feature is determined heuristically in the m ultiple feature-based stereo matching method, it is very difficult to fuse them adequately. In the proposed algorithm, the weight of each fe ature, that is, the relative importance of each feature, is decided fr om the similarity between the intensities in the local region of each left and right wavelet channels. Since the window size used for the de cision of weight and disparity values greatly influences the processed result, the window is adaptively determined from the disparities esti mated in the coarse resolution and low-varying channel of fine resolut ion. The window size must be large enough to obtain signal-to-noise ra tio, but not too large as to induce the effects of projective distorti on. Also, a new relaxation algorithm which can reduce false matches wi thout blurring the disparity edge is proposed. By integrating adaptive weight variable window selection method, and relaxation process, an a ccurate and stable disparity map is obtained. Experimental results for various images show that the proposed algorithm has good performance even if the image has the unfavorable conditions. (C) 1997 Pattern Rec ognition Society.