Significant luminance and chrominance discrepancies between the different camera views can often be observed in multiview video sequences. In this paper

a luminance and chrominance correction algorithm based on partially overlapped local histogram matching is proposed. In the histogram matching method

amapping function is established by matching the histogram of the original image to that of the reference image. Then the mapping function is applied to the original image to obtain the corrected image. There are two branches of histogram matching according to the mapping function used: global histogram matching and adaptive localhistogram matching. Global histogram matching uses the same mapping function for the whole image

so its performance is relatively low. Adaptive local histogram matching can calibrate the luminance and chrominance effectively by using the local histogram for each pixe

l but the computational complexity is very high. In the proposed partially overlapped localhistogram matchingmethod

the samemapping function is applied to a block of pixels. A conditional block reduction filter is utilized on the boundaries of all the adjacentblocks to eliminate the blocking effect. The proposed algorithm can be used as a preprocessing tool in the multiview video system. Experiment results show that it can improve the performance of the multiview video encoder.