scholarly journals Multiframe Super-Resolution of Color Images Based on Cross Channel Prior

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 901
Author(s):  
Shen Shi ◽  
Bing Xiangli ◽  
Zengshan Yin
Keyword(s):  
Color Image ◽  
Super Resolution ◽  
Color Images ◽  
Experimental Results ◽  
Reconstruction Method ◽  
Resolution Method ◽  
The Cross ◽  
Color Channels

Color images have a wider range of applications than gray images. There are two ways to extend the traditional super-resolution reconstruction method to color images: Super resolution reconstructs each channel of the color image individually; Change the RGB color bands into YCrCb color bands, then super-resolution reconstructs the luminance component and interpolates the chrominance components.These algorithms cannot effectively utilize the property that the edges and textures are similar in the RGB channels, and the results of those methods may lead to color artifacts. Aiming to solve these problems, we propose a new super-resolution method based on cross channel prior. First, a cross channel prior is proposed to describe the similarity of gradient in RGB channels. Then, a new super-resolution method is proposed for color images via combination of the cross channel prior and the traditional super-resolution methods. Finally, the proposed method reconstructs the color channels alternately. The experimental results show that the proposed method could effectively suppress the generation of color artifacts and improve the quality of the reconstructed images.

An Efficient Super Resolution Based on Image Dimensionality Reduction Using Accumulative Intensity Gradient

2014 ◽  
Vol 18 (4) ◽  
pp. 518-528 ◽  
Author(s):  
Muhammad Haris ◽  
◽  
Kazuhito Sawase ◽  
Muhammad Rahmat Widyanto ◽  
Hajime Nobuhara ◽  
...  
Keyword(s):  
Color Image ◽  
Super Resolution ◽  
Computation Time ◽  
Color Images ◽  
Natural Images ◽  
Image Generation ◽  
Intensity Gradient ◽  
Resolution Method ◽  
Edge Direction ◽  
Resolution Algorithm

An efficient super resolution algorithm based on edge direction is proposed based on the dimensional reduction of color images and 3 types of edge direction. The basic idea is to reduce image – especially color image – dimensions and to interpolate pixels by using 3 simple edge directions – vertical, horizontal, and diagonal. The proposed algorithm conceivably eliminate more color artifacts than Bicubic. The results of experiments using 30 natural images confirm that PSNR of the proposed method achieve the same quality as Fast Curvature Based Interpolation (FCBI). We confirmed that computation time for the proposed method was 40% shorter for RGB and 20% shorter for grayscale images than the previous fastest method, i.e., FCBI. We show efficient panorama image generation based on the proposed super resolution method as one application of our proposal.

scholarly journals Implementasi Metode Super Resolusi Untuk Meningkatkan Kualitas Citra Hasil Screenshot

2020 ◽  
Vol 7 (3) ◽  
pp. 432
Author(s):  
Windi Astuti
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Super Resolution ◽  
Linear Interpolation ◽  
Resolution Method ◽  
Image Zooming ◽  
Image Enlargement ◽  
Three Stages

Various types of image processing that can be done by computers, such as improving image quality is one of the fields that is quite popular until now. Improving the quality of an image is necessary so that someone can observe the image clearly and in detail without any disturbance. An image can experience major disturbances or errors in an image such as the image of the screenshot is used as a sample. The results of the image from the screenshot have the smallest sharpness and smoothness of the image, so to get a better image is usually done enlargement of the image. After the screenshot results are obtained then, the next process is cropping the image and the image looks like there are disturbances such as visible blur and cracked. To get an enlarged image (Zooming image) by adding new pixels or points. This is done by the super resolution method, super resolution has three stages of completion, first Registration, Interpolation, and Reconstruction. For magnification done by linear interpolation and reconstruction using a median filter for image refinement. This method is expected to be able to solve the problem of improving image quality in image enlargement applications. This study discusses that the process carried out to implement image enlargement based on the super resolution method is then built by using R2013a matlab as an editor to edit programs

Evaluation of the sparse coding super-resolution method for improving image quality of up-sampled images in computed tomography

2017 ◽  
Author(s):  
Junko Ota ◽  
Kensuke Umehara ◽  
Naoki Ishimaru ◽  
Shunsuke Ohno ◽  
Kentaro Okamoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Sparse Coding ◽  
Super Resolution ◽  
Resolution Method

scholarly journals Image Encryption and Decryption using RSA Algorithm with Share Creation Techniques

2019 ◽  
Vol 8 (4) ◽  
pp. 2797-2800
Keyword(s):  
Image Encryption ◽  
Color Image ◽  
Visual Cryptography ◽  
Color Images ◽  
Blue Color ◽  
Image Sharing ◽  
Rsa Algorithm ◽  
Encryption And Decryption ◽  
Is Value

visual cryptography system proposed a image encryption and decryption method. In the proposed method Red, Green, Blue color images using visual cryptography. In existing system is working for share created, it is encrypted separately by using visual secret share creation (VSS) algorithms. The proposed work is original images share1 and ahare2 created XOR-Based visual cryptography. This proposed schemes share1 encryption and share2 encryption included in RSA algorithm. The share1 and ahare2 decryption process is enable secret image sharing and then stacking. The proposed system is value calculate the PSNR and MSE formula and then image security using NPCR and UACI formula. The visual cryptography existing work to compare the proposed work and better results quality of RGB color images. The color image encryption and decryption using RSA algorithm and matlab coding.

scholarly journals Robust Secure Color Image Watermarking Using 4D Hyperchaotic System, DWT, HbD, and SVD Based on Improved FOA Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Hira Nazir ◽  
Imran Sarwar Bajwa ◽  
Muhammad Samiullah ◽  
Waheed Anwar ◽  
Muhammad Moosa
Keyword(s):  
Color Image ◽  
Image Watermarking ◽  
Similarity Index ◽  
Motion Blur ◽  
Optimization Techniques ◽  
Color Images ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
Fruit Fly Optimization Algorithm ◽  
Hyperchaotic System

In the recent past, a different set of algorithms for watermarking and securing the color images have been developed by using transformation, decomposition, and optimization techniques for watermark embedding and extraction. In this paper, we propose an optimized and robust watermarking algorithm coupled with a 4D hyperchaotic system, and its performance is analyzed by extending and differentiating the existing work. Our contribution in the presented work is watermarking and securing the color images by an optimized algorithm that uses transformation technique such as Discrete Wavelet Transformation (DWT) and decomposition techniques such as Hessenberg decomposition (HbD) and singular value decomposition (SVD) coupled with the 4D hyperchaotic system, while the optimization is carried out by improved evolution fruit fly optimization algorithm (IEFOA). The experimental results based on different types of attacks (filter attacks, noise attacks, cropping attack, JPEG compression, motion blur, sharpening, and rotation), key sensitivity, normalized correlation, peak signal-to-noise ratio, and structural similarity index measure are done for measuring the algorithm’s performance regarding invisibility and robustness. The experimental results show that the proposed scheme has excellent invisibility and keeps a good trade-off between invisibility and robustness. The experiment results show that the proposed approach outperforms the previous approaches.

A depth-based super-resolution method for multi-view color images

2016 ◽  
Author(s):  
Jun Fan ◽  
Xiangrong Zeng ◽  
Qizi Huangpeng ◽  
Jinglun Zhou ◽  
Jing Feng
Keyword(s):  
Super Resolution ◽  
Color Images ◽  
Resolution Method

An Effective Regularization Method for Image Super Resolution

2011 ◽  
Vol 219-220 ◽  
pp. 1411-1414
Author(s):  
En Wei Zheng ◽  
Xian Jun Wang
Keyword(s):  
Super Resolution ◽  
License Plate ◽  
Reconstruction Method ◽  
Ill Posed ◽  
High Resolution Images ◽  
Image Super Resolution ◽  
Sr Reconstruction ◽  
Real Traffic ◽  
Reconstruction Model

In this paper, we propose a new super resolution (SR) reconstruction method to handle license plate numbers of vehicles in real traffic videos. Recently, SR reconstruction shemes based on regularization have been demonstrated to be effective because SR reconstrction is an ill-posed problem. Working within this promising framework, the residual data (RD) term can be weighted according to the differences among the observed LR images in the SR reconstruction model. Moreover, L1 norm is used to measure the RD term in order to improve the robustness of our method. Experiments show the proposed method improves the subjective visual quality of the high resolution images.

A New Robust Reversible Blind Watermarking in Wavelet-Domain for Color Images

2016 ◽  
Vol 16 (02) ◽  
pp. 1650006 ◽  
Author(s):  
P. Manimehalai ◽  
P. Arockia Jansi Rani
Keyword(s):  
Clustering Algorithm ◽  
Color Image ◽  
Reversible Watermarking ◽  
Color Images ◽  
Blind Watermarking ◽  
Wavelet Domain ◽  
Wavelet Coefficients ◽  
Recovered Image ◽  
Host Image

Reversible watermarking methods are used for copyright protection and are able to recover the host image without distortion. Robust reversible watermarking technique should resist against intentional and unintentional image processing attacks. Robust reversible watermarking techniques should have three features namely imperceptibility, reversibility and robustness. In this paper, it is proposed to develop a new robust reversible blind watermarking for color images based on histogram construction of the wavelet coefficients constructed from the cover image. In the proposed approach, the red component of a host color image is decomposed into wavelet coefficients. Motivated by the excellent spatio-frequency localization properties of wavelets, this technique is proposed in the wavelet domain. The pixels are adjusted before watermark embedding such that both overflow and underflow of pixels during embedding is avoided and image is recovered without distortion. Based on histogram construction and the local sensitivity of Human Visual System (HVS) in wavelet domain, the watermark is embedded. For watermark extraction without host image, k-means clustering algorithm is proposed. The experimental results show that the proposed technique has good performance in terms of reversibility and robustness with the high quality of the watermarked image. The PSNR value of the recovered image is around 48[Formula: see text]dB which proves that the quality of the recovered image is not degraded.

A COLOR IMAGE RETRIEVAL METHOD BASED ON COLOR MOMENT AND COLOR VARIANCE OF ADJACENT PIXELS

2002 ◽  
Vol 16 (01) ◽  
pp. 113-125 ◽  
Author(s):  
YUNG-KUAN CHAN ◽  
CHIN-CHEN CHANG
Keyword(s):  
Image Retrieval ◽  
Similarity Measure ◽  
Spatial Information ◽  
Color Image ◽  
Image Features ◽  
Experimental Results ◽  
Retrieval Method ◽  
Color Moment

This paper first introduces three simple and effective image features — the color moment (CM), the color variance of adjacent pixels (CVAP) and CM–CVAP. The CM feature delineates the color-spatial information of images, and the CVAP feature describes the color variance of pixels in an image. However, these two features can only characterize the content of images in different ways. This paper hence provides another feature CM–CVAP, which combines both, to raise the quality of similarity measure. The experimental results show that the image retrieval method based on the CM–CVAP feature gives quite an impressive performance.

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