Abstract: The project Assessment of Image Quality Using its Similarities and Deviation in Gradient Metrics is mainly done in order to increase the image quality and also to decrease the resulting time of the processed image for multiple images as input. To evaluate the perceptual quality of the single best output image in many applications such as image restoration, image compression and multimedia streaming. A image quality assessment (IQA) model with computationally efficient and also deliver high quality prediction accuracy. In case processing with images and in other fields the process of working on quality plays of image hits the major role. Likewise major project were based on improving image quality by comparing the spoof images and reference images. In case of existing system there were four techniques like GMSD, PNSR, SSIM and MSE that were used to increase the image quality and resulting time. Yet, the image that is obtained is still not clear due to the use of top-down framework. Hence in order to improvise the existing system, we have created a proposed design to find the best image among multiple images, includes another four techniques like MAMS, SME, SPE, RRED that are used to improve the image quality. The pixel wise similarity between gradient magnitude maps of reference and distorted image is computed .These methods are also helpful in improving the calculating time of the models. These methods are used with high performance IQA applications and with perfect GMSD model.
Keywords: GMSD, PNSR, SSIM and MSE, image quality assessment (IQA).
Title: Improving Image Quality Using Gradient Magnitude Similarity Deviation
Author: Mrs. Benazir Begum.A, Anandraj.D, Arunraj.G, Anitha.D, Swathi.S
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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