Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

Real-World Single Image Super-Resolution: A Brief Review

Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution ones. Recently, the VSR methods based on deep neural networks have made great progress. However, there is rarely systematical review on these methods. In this survey, we comprehensively investigate 37 state-of-the-art VSR methods based on deep learning. It is well known that the leverage of information contained in video frames is important for video super-resolution. Thus we propose a taxonomy and classify the methods into seven sub-categories according to the ways of utilizing inter-frame information. Moreover, descriptions on the architecture design and implementation details are also included. Finally, we summarize and compare the performance of the representative VSR methods on some benchmark datasets. We also discuss the applications, and some challenges, which need to be further addressed by researchers in the community of VSR. To the best of our knowledge, this work is the first systematic review on VSR tasks, and it is expected to make a contribution to the development of recent studies in this area and potentially deepen our understanding of the VSR techniques based on deep learning. 

Video super-resolution based on deep learning: a comprehensive survey

The discrete cosine transform (DCT), introduced by Ahmed, Natarajan and Rao, has been used in many applications of digital signal processing, data compression and information hiding. There are four types of the discrete cosine transform. In simulating the discrete cosine transform, we propose a generalized discrete cosine transform with three parameters, and prove its orthogonality for some new cases. A new type of discrete cosine transform is proposed and its orthogonality is proved. Finally, we propose a generalized discrete W transform with three parameters, and prove its orthogonality for some new cases. Keywords: Discrete Fourier transform, discrete sine transform, discrete cosine transform, discrete W transform Nigerian Journal of Technological Research , vol7(1) 2012

On discrete cosine transform

https://research.edgehill.ac.uk/files/46422294/1_s2.0_S1566253521001792_main.pdf

Real-world single image super-resolution: A brief review

Super-resolution includes the techniques which deal with the methods of converting the low-resolution image into the high-resolution image. In this paper, various challenges affecting the implementation of Super-Resolution (SR) along with the detailed survey of SR implementation methods have been presented. Different issues related to the SR have been explored from literature which are limiting the SR implementations. Besides, there are also various techniques to implement the SR, detailed survey of these techniques along with comparison, have been included in this paper. In this work main focus has been given to a single image based super-resolution as it is the more practical type of super-resolution. The basic purpose of the paper is exploring the various possibilities of SR along with practical constraints.

Survey on Single Image based Super-resolution — Implementation Challenges and Solutions

Image denoising is the first preprocessing step dealing with image processing. In image denoising an image is processed using certain restoration techniques to remove induced noise which may creep in the image during acquisition, transmission or compression process. Examples of noise in an image can be Additive White Gaussian Noise (AWGN), Impulse Noise, etc. The goal of restoration techniques is to obtain an image that is as close to the original input image as possible. In this paper objective evaluation methods are used to judge the efficiency of different types of spatial domain filters applied to different noise models, with a quantitative approach. Performance of each filter is compared as they are applied on images affected by a wide variety of noise models. Conclusions are drawn in the end, about which filter is best suited for a number of noise models individually induced in an image, according to the experimental data obtained.

Image denoising using spatial domain filters: A quantitative study

One of the major drawbacks of the block-based DCT compression methods is that it may result in visible artifacts at block boundaries due to coarse quantization of the coefficients. This paper proposes a new adaptive post-filtering algorithm to remove coding artifacts in block-based DCT compressed images. Presence of blocking artifacts is detected using block activity based on human visual system and block statistics. The boundary regions between the blocks are identified as smooth, non-smooth or intermediate regions. The blocking artifact in the smooth and non-smooth regions are removed by modifying a few DCT coefficients while an edge preserving smoothing filter is applied to the intermediate region. Experimental results illustrating the performance of proposed method on the basis of PSNR, MOS, MSSIM, SF, and BBM indices are presented and evaluated. Compared with other methods, the proposed one achieves better detail preservation and artifact removal performance with lower computational complexity.

A signal adaptive filter for blocking effect reduction of JPEG compressed images

In this paper, review and analysis of major image interpolation techniques have been presented. Image interpolation is very useful for fast super resolution (SR) of images. In super resolution a low resolution image is converted to a high resolution image. There are a number of methods to implement the Super resolution, However, the fastest method of SR implementation is always interpolation. In the presented work comparison of the major methods in the field of interpolation has been given. Moreover, simulations of different image interpolation techniques have been implemented for the comparison. The simulation results of the different methods have been compared based on the PSNR, MSE and MSSIM quality matrices.

Review and Comparative analysis of various Image Interpolation Techniques

Objectives: This paper is providing a comparative performance analysis of wavelet denoising with Gaussian filter applied on images contaminated with various noises. Gaussian filter is a basic filter used in image processing. Its response is varying with its kernel sizes that have also been shown in analysis. Wavelet based de-noising is also one of the way of removing various noises usually present in images. Wavelet transform is used to convert the images to wavelet domain. Based on thresholding operations in wavelet domain noise could be removed from images. Methods/Analysis: In this paper, image quality matrices like PSNR and MSE have been compared for the various types of noises in images for different denoising methods. Moreover, the behavior of different methods for image denoising have been graphically shown in paper with MATLAB based simulations. Findings: In the end wavelet based de-noising methods has been compared with Gaussian based filter. The paper provides a review of filters and their denoising analysis under different noise conditions.

Comparative Analysis of Gaussian Filter with Wavelet Denoising for Various Noises Present in Images

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