在自由视点视频系统中,如何能在视频终端得到高质量的视频图像已成为基于深度图的绘制(DIBR)技术所研究的主要任务,其中虚拟视点像素插值是该技术中影响绘制质量的一个重要环节。针对虚拟视点绘制标准方案中存在的问题,提出了一种基于空间加权的像素插值算法。它是通过对多个投影像素点的深度值和水平方向绝对距离进行加权操作来实现像素插值的。在插值过程中,该算法考虑了不同区域投影像素点个数对像素插值准确性的影响,从而剔除了部分失真像素点,并且在图像输出前还分别对左、右参考虚拟视点进行了失真检测和矫正。实验结果表明,该算法改善了绘制的主、客观质量,其中,PSNR平均提高0.30 d B,SSIM平均提高0.001 3。因此,该算法可以有效地抑制像素插值过程引入的噪声,提高像素插值的精度。
Most of Image Quality Assessment (IQA) metrics consist of two processes. In the first process, quality map of image is measured locally. In the second process, the last quality score is converted from the quality map by using the pooling strategy. The first process had been made effective and significant progresses, while the second process was always done in simple ways. In the second process of the pooling strategy, the optimal perceptual pooling weights should be determined and computed according to Human Visual System (HVS). Thus, a reliable spatial pooling mathematical model based on HVS is an important issue worthy of study. In this paper, a new Visual Perceptual Pooling Strategy (VPPS) for IQA is presented based on contrast sensitivity and luminance sensitivity of HVS. Experimental results with the LIVE database show that the visual perceptual weights, obtained by the proposed pooling strategy, can effectively and significantly improve the performances of the IQA metrics with Mean Structural SIMilarity (MSSIM) or Phase Quantization Code (PQC). It is confirmed that the proposed VPPS demonstrates promising results for improving the performances of existing IQA metrics.
trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.
