A Comparative Study on Different Genres of Image Restoration Techniques

2019 ◽  
pp. 373-383 ◽  
Author(s):  
Monica Singh ◽  
Sujala Pradhan ◽  
Md Ruhul Islam ◽  
N. Chitrapriya
Keyword(s):  
Comparative Study ◽  
Image Restoration ◽  
Restoration Techniques

scholarly journals Comparative Study of Major Image Enhancement Algorithms

2017 ◽  
Vol 2 (7) ◽  
pp. 23
Author(s):  
Amrutha Kulkarni ◽  
Shanta Rangaswamy ◽  
Manonmani S
Keyword(s):  
Comparative Study ◽  
Image Restoration ◽  
Image Enhancement ◽  
Original Image ◽  
Inverse Process ◽  
Restoration Techniques

Image restoration is a process of reconstruction or recovery of an image that has been corrupted or degraded by any degradation phenomenon. Image restoration techniques are inclined towards modeling the degradation and applying the inverse process in order to recover the original image. The critical goal of restoration techniques is to improve the quality of an image in some predefined manner. This present paper is a comparative study of image enhancement techniques used for improving the quality of a given image and evaluate it against the quality of a given image and evaluate it against SNR, PSNR, MSE, and SSIM as metrics.

scholarly journals Analysis and Comparative Study of Image Restoration by using Matlab

2018 ◽  
Vol Volume-2 (Issue-4) ◽  
pp. 1259-1263
Author(s):  
Vaishali Kumari ◽  
Ranjan Kumar Singh ◽  
Keyword(s):  
Comparative Study ◽  
Image Restoration

A Comparative Study of Image Deblurring Techniques

2020 ◽  
Vol 17 (9) ◽  
pp. 4571-4579
Author(s):  
Rajbir Singh ◽  
Sumit Bansal
Keyword(s):  
Comparative Study ◽  
Image Restoration ◽  
Digital Image ◽  
Minimum Mean Square Error ◽  
Direct Methods ◽  
Structural Similarity ◽  
Single Step ◽  
Noise Model ◽  
Image Deconvolution ◽  
Indirect Methods

The method of recovering a true image from degraded one, to analyze that digital image and characteristics with no artifact errors is known as Image Restoration. These techniques are of two types: direct methods and indirect methods. Direct methods are those in which the results of image restoration are produced in one single step. Indirect methods are those in which the results of image restoration are produced after various steps. This method is termed as blind image deconvolution, when the known info is just the blurred digital image and no info about the (Point Spread Function) (PSF) or the degrading model. The target of the procedure is to recover both the latent (un-blurred) image and the blur kernel, simultaneously. In this paper, we presented a comprehensive research of image noise model,de-blurring methods, blur types, and a comparative study of various deblurring methods. We have implemented number experiments to study these methods according to their performance, (Peak Signal to Noise Ratio) PSNR, (structural similarity) SSIM, blur type, and (Minimum Mean Square Error) MMSE.

scholarly journals Image Dehazing Based on Physical Model and Gray Projection

2019 ◽  
Vol 9 (1S3) ◽  
pp. 241-245
Keyword(s):  
Image Restoration ◽  
Physical Model ◽  
Dark Channel Prior ◽  
Image Dehazing ◽  
Dark Channel ◽  
Restoration Techniques ◽  
Image Computation ◽  
Computing Speed ◽  
Atmospheric Light

The climatic scattering and ingestion offer climb to the ordinary marvel of obscurity, which truly impacts the detectable quality of view. Dehazing is the technique used to expel the dimness. In late year, various works have been done to improve the detectable quality of picture taken under horrible climate. The images that are taken under overcast conditions experience the evil impacts of shading contortion and attenuation. The proposed strategy is in light of the Dark Channel Prior speculation and gray projection. The transmission map is resolved using the determined estimation of atmospheric light. It uses box filter to lessen the complexity and to improve the computing speed. This computation can restore image with incredible quality and the speed of image computation is high. The proposed strategy is differentiated with other image enhancement strategies and image restoration techniques. It is likewise exceptionally proficient technique since it can process huge images within less time.

scholarly journals Exploring Image Processing and Image Restoration Techniques

2015 ◽  
Vol 15 (3) ◽  
pp. 172-179
Author(s):  
Batyrkhan Sultanovich Omarov ◽  
Aigerim Bakatkaliyevna Altayeva ◽  
Young Im Cho
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Restoration Techniques

Image Restoration using Recent Techniques: A Survey

2021 ◽  
pp. 13050-13062
Author(s):  
Mrs. Poonam Y. Pawar, Dr. Bharati Sanjay Ainapure
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Digital Image ◽  
Medical Science ◽  
Computer Algorithms ◽  
Original Image ◽  
Performance Improvements ◽  
Restoration Techniques ◽  
Degraded Image ◽  
Recent Trends

Image Restoration is one of the challenging and essential milestones in the image processing domain. Digital image processing is a technique for manipulating digital images using a variety of computer algorithms. The process of transforming the degraded or damaged image to the original image can be known as Image Restoration. The image restoration process improves image quality by converting the degraded image into the original clean image. The techniques for image restoration are comprised of predefined parameters through which digital image gets processed for refinements. The purpose of restoration is to start with the acquired image and then estimate the original image as accurately as possible. A degraded image can be contaminated by any of a blur or noise or both. Many factors can contribute to image degradation, including poor capture, poor lighting, and poor eyesight. Medical science, defensive sensor systems, forensic detections, and astrology all rely on image restoration for accuracy. This paper discusses various image restoration techniques using recent trends for performance improvements.

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