Comparative study of Structural Similarity Index (SSIM) by using different edge detection approaches on live video frames for different color models

Evaluation the quality of the video frame is a complex and hard process since human's opinion is affected by physical and psychological parameters. Various procedures are proposed for evaluating the quality of the video frame. Video frame quality assessment plays a vital role in the field of video processing. Structural Similarity Index (SSIM) has become a standard among image quality metrics. Structural Similarity Index is a framework for quality evaluation based on the degradation of structural information of video frame. Structural Similarity Index is used to assess the similarity between the reference video frame and the processed video frame. Structural Similarity Index is easy and well linked with subject evaluation. Measure of structural similarity index is able to provide a good approximation to perceived image quality. This procedure evaluates the visual impact of changes in luminance, contrast and structure in an image. In this paper SSIM values are calculated and compared for live video frames by applying different edge detection operators for different color models to assess the quality of the frames. Experimental results comparisons demonstrate the effectiveness of the proposed method.