Bi-featured image quality assessment with the hierarchical image quality enhancement algorithm

摘要

The image quality assessment techniques are the methods to evaluate the quality of the image matrix. The image quality assessment methods are applied to evaluate the overall quality of the image matrices and indicate the presence of the noise, blur or other dispatternised elements. Using image quality assessment the level of noise, blur and other elements can be studied. The image quality assessment method in the proposed model includes the hybridization of the horizontal and vertical quality assessment along with the diagonal and anti-diagonal quality assessment. Both of the indices play the vital role in the removal of the noise from the input image matrix using the image quality enhancement methods. The image quality is enhanced by using the combination of the low rank matrix recovery along with the Non-reference image restoration algorithm. The incorporation of the histogram equalization method adds the additional improvement to the overall design by normalizing the color illumination effect over the corrected image using the latter methods. The adaptive intensity based image restoration has been applied using the proposed solution, where input is taken from the multi-dimensional and multi-directional image quality assessment algorithm in this model. Several experiments have been conducted over the binary matrix to evaluate the overall performance of the matrix reconstruction system. The proposed model performance has been recorded in the adequately well measures, which indicates the robustness of the proposed model.