Performance Evaluation of Structural Similarity Index Metric in Different Colorspaces for HVS Based Assessment of Quality of Colour Images

The evaluation of visual quality of color images has become very important and challenging task due to explosion of multimedia and graphics content on internet. An image exhibits loss in color information due to introduction of noise, blur, blocking artefacts, channel distortion and also during lossy compression. The primary goal of Image Quality Metric (IQM) is to measure emergence of such distortion and evaluate the image quality where the outcome is validated by its consistency with Human Visual System (HVS). In response to this need, researchers have developed many objective and subjective image quality assessment metrics. But most of the available assessment models measure the quality of color image by using the intensity plane of the image ignoring loss in color. This paper presents performance comparison of evaluation of quality of color image using Structural Similarity Index Metric (SSIM) based on luminance and color information computed in different HVS consistent colorspaces against subjective quality data. Results obtained through experimentation in YCbCr, HSI, YUV, YIQ and CIELab colorspace show that when color information is included in quality assessment, quality score of the metric becomes highly consistent with Human Visual System (HVS). Further it has been observed that SSIM calculated in CIELab colorspace is highly correlated with Differential Mean Opinion Score (DMOS) for all types of distortions used in experimentation. KeywordsYIQ, HSI, YCbCr, DMOS, quality, SSIM, HVS, IQM, CIELab