Hybrid Adaptive Image Restoration Method with Pixel Block Estimation and Histogram Equalization
Author(s) -
Sukhwinder Singh,
Amit Grover
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016911144
Subject(s) - adaptive histogram equalization , computer science , histogram equalization , block (permutation group theory) , equalization (audio) , pixel , histogram , histogram matching , artificial intelligence , computer vision , image (mathematics) , estimation , pattern recognition (psychology) , telecommunications , mathematics , channel (broadcasting) , geometry , management , economics
The process of recovering image from corrupted state is called restoration. In this paper, the combination of the neighbor based reference model and non-reference image matrix enhancement is proposed for the enhancement of the results. In this paper the restoration with image missing pixel recovery and recreation is done and non-reference restoration enhancement method is used to recover the pixel expansion problem. Then image is more enhanced by using Histogram. The experimental results have been executed over the grayscale standard images of the Lena and Barbara. The results have shown that the proposed model outperforms the existing models when evaluated on the basis of peak signal to noise ratio and mean squared error.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom