关键词: 图像质量评价, 结构相似度, 尺度不变特征变换, 视觉重要性, 人眼视觉系统

Abstract: In order to overcome the deficiency of the weighted average strategy which is adopted in the structure similarity algorithm for the perception of image quality, considering that certain regions in an image may not bear the same importance as others, an image quality assessment metric based on local invariant features was put forward. The algorithm used structural similarity to calculate the quality map of distorted image, and then extracted the local invariant features points in the distorted image. The region around features points was given more visual importance, and the quality of the image distortion could be evaluated by using integrated weighting strategy. The experimental results on the standard image library show that the computational complexity of this algorithm is relatively lower and the evaluation performance of structure similarity algorithm can be considerably increased, which achieves better consistency with the subjective assessment of human eyes.

Key words: image quality assessment, Structural Similarity(SSIM), Scale Invariant Features Transform(SIFT), visual importance, Human Visual System