Histogram-Based Prefiltering for Luminance and Chrominance Compensation of Multiview Video

Significant advances have recently been made in the coding of video data recorded with multiple cameras. However, luminance and chrominance variations between the camera views may deteriorate the performance of multiview codecs and imagebased rendering algorithms. A histogram matching algorithm can be applied to efficiently compensate for these differences in a prefiltering step. A mapping function is derived which adapts the cumulative histogram of a distorted sequence to the cumulative histogram of a reference sequence. If all camera views of a multiview sequence are adapted to a common reference using histogram matching, the spatial prediction across camera views is improved. The basic algorithm is extended in three ways: a time-constant calculation of the mapping function, RGB color conversion, and the use of global disparity compensation. The best coding results are achieved when time-constant histogram calculation and RGB color conversion are combined. In this case, the usage of ...

• Type: Journal
• Year: 2008
• Where: TCSV
• Authors: Ulrich Fecker, Marcus Barkowsky, André Kaup
• Keywords: Camera, Cumulative Histogram, Histogram, TCSV 2008