A least-squares-based 2-D filtering for disparity estimation

A block-matching method is generally used for the disparity estimation as well as motion estimation applications. However, this method suffers from limitations such as blocking artifacts on the reconstructed images and a lack of compensation ability for the mismatching areas. A new disparity estimation scheme using 2-D filtering is proposed to provide more accurate estimates of the disparity vector and better compensation ability. This is accomplished by applying the left image to the reference input of the filter while using the right image as the desired output. The goal is to provide the best matching for the right image using the filter output instead of the left image directly as used in the block-matching method. A reduced order filtering scheme is also introduced to minimize the number of filter coefficients for the reconstruction. The reconstructed images generated based upon the estimated disparity vectors and some principal filter coefficients exhibited excellent quality