Improved Color Image Quality Assessment Based on Structural Similarity
Date Issued
2010
Date
2010
Author(s)
Wu, Yi-Ching
Abstract
Image quality assessment (IQA) plays an important role in various image processing applications. In recent years, the research of objective image quality metrics has been developed widely. Human Visual System (HVS) based image quality assessments take the place of simple methods based on absolute difference between pixels of two images (such as MSE and PSNR). In other words, we hope that result of objective evaluation is consistent with human subjective opinion.
We introduce Structural SIMilarity (SSIM) based full-reference image quality measurement. The score of SSIM depends on perceptual similarity of structural information between reference image and distorted image. SSIM has better performance than PSNR (or MSE). Many improved methods based on SSIM are proposed one by one. For example, those methods consider the human emphatic features. Multi-scale SSIM provides more flexibility than single-scale SSIM. Those improved algorithms provide better performance than original SSIM.
Most image quality assessments are applied in gray-level images. However, color image is widely used in recent years. Color is also an important feature of an image. It is necessary to develop image quality assessment to perform in color image. We propose an improved color image quality algorithm to deal with color images. In our simulation, we can see the better result of algorithm after considering color feature of image. The result after adding our proposed algorithm is more consistent with human subjective perception than original algorithm.
Subjects
image quality assessment (IQA)
human visual system (HVS)
perceptual quality
structural similarity (SSIM)
image analysis
color image
Type
thesis
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