多视点视频中基于局部直方图匹配的亮度和色差校正

由于相机性能的差异,多视点视频序列之间总是存在亮度和颜色的差异,为降低这种差异对多视点系统中各种后续处理效果的影响,提出了一种基于部分重叠局部直方图匹配的亮度和色差校正算法。该直方图匹配算法先通过原图像直方图和参考图像直方图的匹配建立映射函数,然后使用该映射函数来校正原图像的亮度和色差值。根据映射函数的计算方法不同,直方图匹配可以分为全局直方图匹配和局部自适应直方图匹配。在全局直方图匹配算法中,由于整幅图像是使用统一的映射函数,因此校正性能较差。而局部自适应直方图匹配算法则是利用局部信息为每个像素建立唯一的映射函数,因此能够准确地校正图像不同区域的差异,但是算法的复杂度非常高。该部分交叠的局部直方图匹配方法中,一小块范围内的像素是使用同样的局部直方图来建立映射函数,然后使用条件去块滤波器去除可能存在的块效应。与自适应局部直方图匹配算法相比,该算法不仅可减少计算直方图和映射函数的次数,而且在降低计算复杂度的同时,还能够自适应地校正图像不同区域的差异。该算法可作为多视点视频系统中的预处理技术,实验结果表明,该算法能够提高后续压缩过程的性能。

Luminance and Chrominance Correction for Multi-view Video Using Overlapped Local Histogram Matching

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, a mapping 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 local histogram 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 pixel,but the computational complexity is very high.In the proposed partially overlapped local histogram matching method,the same mapping function is applied to a block of pixels.A conditional block reduction filter is utilized on the boundaries of all the adjacent blocks 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.