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首页> 外文会议>2018 IEEE 17th International Conference on Mathematical Methods in Electromagnetic Theory >Structural Similarity Index with Predictability of Image Blocks
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Structural Similarity Index with Predictability of Image Blocks

机译：具有图像块可预测性的结构相似性指数

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摘要

Structural similarity index (SSIM) is a widely used full-reference metric for assessment of visual quality of images and remote sensing data. It is calculated in a block-wise manner and is based on multiplication of three components: similarity of means of image blocks, similarity of contrasts and a correlation factor. In this paper, two modifications of SSIM are proposed. First, a fourth multiplicative component is introduced to SSIM (thus obtaining SSIM4) that describes a similarity of predictability of image blocks. A predictability for a given block is calculated as a minimal value of mean square error between the considered block and the neighboring blocks. Second, a simple scheme for calculating the metrics SSIM and SSIM4 for color images is proposed and optimized. Effectiveness of the proposed modifications is confirmed for the specialized image databases TID2013, LIVE, and FLT. In particular, the Spearman rank order correlation coefficient (SROCC) for the recently introduced FLT Database, calculated between the proposed metric color SSIM4 and mean opinion scores (MOS), has reached the value 0.85 (the best result for all compared metrics) whilst for SSIM it is equal to 0.58.
机译：结构相似性指数（SSIM）是一种广泛使用的全参考指标，用于评估图像和遥感数据的视觉质量。它以逐块方式计算，并且基于三个分量的乘积：图像块均值的相似度，对比度的相似度和相关因子。本文提出了对SSIM的两种修改。首先，将第四乘法组件引入SSIM（从而获得SSIM4），该组件描述图像块的可预测性的相似性。给定块的可预测性被计算为所考虑的块与相邻块之间的均方误差的最小值。其次，提出并优化了一种简单的计算彩色图像指标SSIM和SSIM4的方案。对于专用图像数据库TID2013，LIVE和FLT，确认了所提出的修改的有效性。特别是，新近引入的FLT数据库的Spearman等级相关系数（SROCC），在建议的度量颜色SSIM4和平均意见得分（MOS）之间进行计算，已达到0.85（所有比较度量的最佳结果），而对于SSIM等于0.58。

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