Novel Evaluation Index for Image Quality

Abstract

Indexes used for image quality evaluation are provided as computational models to measure the quality of images in a perceptually consistent manner. This paper presents a novel evaluation index for assessing image qualities. The index is a modification of the existing traditional Structural Similarity Index Measure (SSIM) by adding another factor to reflect the shape of the brightness histogram of the assessed image. The proposed index therefore is a combination of four major factors luminance, contrast, structure and shape of histogram. This index is mathematically simple and applicable in various image processing. For demonstration a new image de-noising approach using an adaptive shrinkage threshold in the shearlet domain is used. Experimental results show that the new image quality indexes give better prediction accuracy, better prediction monotonicity than PSNR, HQI, UIQI and SSIM.