scholarly journals Review of Inpainting Algorithms for Wireless Communication Application

2020 ◽  
Vol 10 (3) ◽  
pp. 5790-5795
Author(s):  
V. Yatnalli ◽  
B. G. Shivaleelavathi ◽  
K. L. Sudha
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Wireless Communication ◽  
Image Compression ◽  
Image Restoration ◽  
Digital Image ◽  
Image Inpainting ◽  
Wireless Channel ◽  
Image Recovery

Digital image inpainting is a technique of restoring large removed /damaged regions of an image with the data from the surrounding pixels of the removed region. The issue of image restoration with inpainting techniques occurs commonly in computer vision/image processing when unwanted objects have to be removed from images, for filling cracks in photographs, etc. Digital image inpainting approach is an active field of research in two significant applications of wireless communication: image compression and image recovery from a damaged image due to errors in a wireless channel. This work presents a brief survey of different image inpainting techniques and their contributions to different wireless communication applications.

scholarly journals Fast Transforms in Image Processing: Compression, Restoration, and Resampling

2014 ◽  
Vol 2014 ◽  
pp. 1-23 ◽  
Author(s):  
Leonid P. Yaroslavsky
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Image Restoration ◽  
Compressive Sensing ◽  
Adaptive Filters ◽  
Processing Methods ◽  
Fast Transforms ◽  
Image Transforms

Transform image processing methods are methods that work in domains of image transforms, such as Discrete Fourier, Discrete Cosine, Wavelet, and alike. They proved to be very efficient in image compression, in image restoration, in image resampling, and in geometrical transformations and can be traced back to early 1970s. The paper reviews these methods, with emphasis on their comparison and relationships, from the very first steps of transform image compression methods to adaptive and local adaptive filters for image restoration and up to “compressive sensing” methods that gained popularity in last few years. References are made to both first publications of the corresponding results and more recent and more easily available ones. The review has a tutorial character and purpose.

Digital Image Zero-Watermarking Algorithm Based on Improved Wavelet Moment

2013 ◽  
Vol 347-350 ◽  
pp. 3232-3236
Author(s):  
Zheng Bao Zhang ◽  
Chao Jia
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Real Time ◽  
Digital Watermarking ◽  
Digital Image ◽  
Image Rotation ◽  
The Real ◽  
Geometric Attacks ◽  
Zero Watermarking ◽  
Local Distortions

Lots of anti-RST attacks watermarking algorithms have been proposed, but few solutions for local geometric attacks, in this paper it proposed a new algorithm combined with the the Wavelet Moment for an anti-geometric attacks. Since wavelet moment was proposed, it is widely used in the field of computer vision, image processing, but the large amount of computation must be improved to be applied to digital watermarking technology so that it can adapt to the real-time detection of digital watermarking. By image rotation, scaling, translation, shear, local distortions, filtering attack operations and so on, these attacks can be seen that the algorithm has good robustness, and the efficiency of watermark detection is relatively high. The experiments show that the algorithm is robustness, greatly accelerate the speed of operation, to unify the robust and efficient.

scholarly journals Quality Improvement for Exemplar-based Image Inpainting using a Modified Searching Mechanism

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Mariwan Wahid Ahmed ◽  
Alan Anwer Abdulla
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Euclidean Distance ◽  
Image Inpainting ◽  
Input Image ◽  
Second Step ◽  
Research Areas ◽  
Potential Applications ◽  
Priority Function ◽  
Popular Images

Digital image processing has a significant impact in different research areas including medical image processing, biometrics, image inpainting, object detection, information hiding, and image compression. Image inpainting is a science of reconstructing damaged parts of digital images and filling-in regions in which information are missing which has many potential applications such as repairing scratched images, removing unwanted objects, filling missing area, and repairing old images. In this paper, an image inpainting algorithm is developed based on exemplar, which is one of the most important and popular images inpainting technique, to fill-in missing area that caused either by removing unwanted objects, by image compression, by scratching image, or by image transformation through internet. In general, image inpainting consists of two main steps: The first one is the priority function. In this step, the algorithm decides to select which patch has the highest priority to be filled at the first. The second step is the searching mechanism to find the most similar patch to the selected highest priority patch to be inpainted. This paper concerns the second step and an improved searching mechanism is proposed to select the most similar patch. The proposed approach entails three steps: (1) Euclidean distance is used to find the similarity between the highest priority patches which need to be inpainted with each patch of the input image, (2) the position/location distance between those two patches is calculated, and (3) the resulted value from the first step is summed with the resulted value obtained from the second step. These steps are repeated until the last patch from the input image is checked. Finally, the smallest distance value obtained in step 3 is selected as the most similar patch. Experimental results demonstrated that the proposed approach gained a higher quality in terms of both objectives and subjective compared to other existing algorithms.

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.

A Research for Image Defogging Algorithm

2013 ◽  
Vol 409-410 ◽  
pp. 1653-1656 ◽  
Author(s):  
Yu Fan ◽  
Xue Feng Wu
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Physical Model ◽  
Digital Image Processing ◽  
Digital Image ◽  
Computational Photography ◽  
Processing Technology ◽  
Image Process ◽  
Image Defogging ◽  
Resolution Algorithm

Computational photography and image processing technology are used to restore the clearness of images taken in fog scenes autmatically.The technology is used to restore the clearness of the fog scene,which includes digital image processing and the physical model of atmospheric scattering.An algorithm is designed to restore the clearness of the fog scene under the assumption of the albedo images and then the resolution algorithm is analysised.The algorithm is implemented by the software of image process ,which can improve the efficiency of the algorithm and interface.The fog image and defogging image are compared, and the results show that the visibility of the image is improved, and the image restoration is more clearly .

JPEG DCT Compressiom

2013 ◽  
Vol 712-715 ◽  
pp. 2542-2545
Author(s):  
Hong Li Jia ◽  
Qiang Liu
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Discrete Cosine Transform ◽  
Digital Image ◽  
Cosine Transform ◽  
Rapid Spread ◽  
Multimedia Technologies ◽  
Joint Photographic Experts Group ◽  
Digital Image Compression ◽  
Further Development

With the rapid spread of image processing applications and the further development of multimedia technologies, compression standards become more and more important. This paper intends to explain JPEG (Joint Photographic Experts Group) compression, which is currently a worldwide standard for digital image compression, is based on the discrete cosine transform (DCT). Based on the research, the paper describes theory and algorithms of the JPEG DCT compression and implements a baseline JPEG codec (encoder/decoder) with MATLAB.

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