scholarly journals Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Liu Lixin ◽  
Guo Feng ◽  
Wu Jinqiu
Keyword(s):  
Image Quality ◽  
Correlation Coefficient ◽  
Compression Ratio ◽  
Search Range ◽  
Fractal Coding ◽  
Acoustic Image ◽  
Image Encoding ◽  
Underwater Acoustic ◽  
Large Size ◽  
Matching Strategy

It is difficult for the conventional image compression method to achieve good compression effect in the underwater acoustic image (UWAI), because the UWAI has large amount of noise and low correlation between pixel points. In this paper, fractal coding is introduced into UWAI compression, and a fractal coding algorithm based on interest region is proposed according to the importance of different regions in the image. The application problems of traditional quadtree segmentation in UWAIs was solved by the range block segmentation method in the coding process which segmented the interest region into small size and the noninterest region into large size and balanced the compression ratio and the decoded image quality. This paper applies the classification, reduction codebook, and correlation coefficient matching strategy to narrow the search range of the range block in order to solve the problem of the long encoding time and the calculation amount of encoding process is greatly reduced. The experimental results show that the proposed algorithm improves the compression ratio and encoding speed while ensuring the image quality of important regions in the UWAI.

scholarly journals Pre and Postprocessing for JPEG to Handle Large Monochrome Images

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 255 ◽  
Author(s):  
Walaa Khalaf ◽  
Abeer Al Gburi ◽  
Dhafer Zaghar
Keyword(s):  
Image Quality ◽  
Image Compression ◽  
Compression Ratio ◽  
Rapid Development ◽  
Reconstructed Image ◽  
Hyperbolic Function ◽  
Image Size ◽  
New Techniques ◽  
Large Size

Image compression is one of the most important fields of image processing. Because of the rapid development of image acquisition which will increase the image size, and in turn requires bigger storage space. JPEG has been considered as the most famous and applicable algorithm for image compression; however, it has shortfalls for some image types. Hence, new techniques are required to improve the quality of reconstructed images as well as to increase the compression ratio. The work in this paper introduces a scheme to enhance the JPEG algorithm. The proposed scheme is a new method which shrinks and stretches images using a smooth filter. In order to remove the blurring artifact which would be developed from shrinking and stretching the image, a hyperbolic function (tanh) is used to enhance the quality of the reconstructed image. Furthermore, the new approach achieves higher compression ratio for the same image quality, and/or better image quality for the same compression ratio than ordinary JPEG with respect to large size and more complex content images. However, it is an application for optimization to enhance the quality (PSNR and SSIM), of the reconstructed image and to reduce the size of the compressed image, especially for large size images.

An Improved Method for CT Image Coding Using PSNR Prediction Model Based on ELM

2015 ◽  
Vol 738-739 ◽  
pp. 598-601
Author(s):  
Han Yang Zhu ◽  
Xin Yu Jin ◽  
Jian Feng Shen
Keyword(s):  
Computational Complexity ◽  
Prediction Model ◽  
Image Coding ◽  
Region Of Interest ◽  
Image Encoding ◽  
Large Size ◽  
Learning Machine ◽  
Intractable Problem ◽  
Encoding Efficiency ◽  
Better Than

In telemedicine, medical images are always considered very important telemedicine diagnostic evidences. High transmission delay in a bandwidth limited network becomes an intractable problem because of its large size. It’s important to achieve a quality balance between Region of Interest (ROI) and Background Region (BR) when ROI-based image encoding is being used. In this paper, a research made on balancing method of LS-SVM based ROI/BR PSNR prediction model to optimize the ROI encoding shows it’s much better than conventional methods but with very high computational complexity. We propose a new method using extreme learning machine (ELM) with lower computational complexity to improve encoding efficiency compared to LS-SVM based model. Besides, it also achieves the same effect of balancing ROI and BR.

Lossy Three-dimensional JPEG2000 Compression of Abdominal CT Images: Assessment of the Visually Lossless Threshold and Effect of Compression Ratio on Image Quality

Radiology ◽  
2007 ◽  
Vol 245 (2) ◽  
pp. 467-474 ◽  
Author(s):  
Helmut Ringl ◽  
Ruediger E. Schernthaner ◽  
Christiane Kulinna-Cosentini ◽  
Michael Weber ◽  
Cornelia Schaefer-Prokop ◽  
...  
Keyword(s):  
Image Quality ◽  
Compression Ratio ◽  
Three Dimensional ◽  
Ct Images ◽  
Abdominal Ct ◽  
Jpeg2000 Compression

Diagnosis of glaucoma using telemedicine – the effect of compression on the evaluation of optic nerve head cup–disc ratio

2000 ◽  
Vol 6 (1_suppl) ◽  
pp. 123-125 ◽  
Author(s):  
Danielle Beauregard ◽  
John Lewis ◽  
Marc Piccolo ◽  
Harold Bedell
Keyword(s):  
Optic Nerve ◽  
Image Quality ◽  
Optic Nerve Head ◽  
Compression Ratio ◽  
Optical Resolution ◽  
Jpeg Images ◽  
Disk Space ◽  
Blinded Observer ◽  
Tiff Format

A photograph of the optic nerve head requires a lot of disk space (over 1 MByte) for storage and may require substantial bandwidth and time for transmission to a remote practitioner for a second opinion. To test whether compression degrades the image quality of the images, 302 slides were digitized at an optical resolution of 2400 pixels/inch (945 pixels/cm) and 30 bit/pixel. The images were saved both in non-compressed TIFF format and in compressed JPEG (compression ratio of 60) format. A blinded observer measured the optic nerve head cup–disc ratio for all three groups: the original slides, uncompressed TIFF and compressed JPEG images. The results showed that digital images were less accurate than slides. However, compression, even up to a ratio of 40, did not make matters worse.

scholarly journals Nouvelle approche d’accélération du codage fractal d’images

2009 ◽  
Vol Volume 11, 2009 - Special... ◽  
Author(s):  
Sofia Douda ◽  
Abdelhakim El Imrani ◽  
Mohammed Limouri
Keyword(s):  
Computational Complexity ◽  
Image Quality ◽  
Compression Ratio ◽  
Classification Methods ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Fast Decoding ◽  
Reduction Methods ◽  
Speed Up ◽  
International Audience

International audience The Fractal image compression has the advantage of presenting fast decoding and independent resolution but it suffers of slow encoding phase. In the present study, we propose to reduce the computational complexity by using two domain pools instead of one domain pool and encoding an image in two steps (AP2D approach). AP2D could be applied to classification methods or domain pool reduction methods leading to more reduction in encoding phase. Indeed, experimental results showed that AP2D speed up the encoding time. The time reduction obtained reached a percentage of more than 65% when AP2D was applied to Fisher classification and more than 72% when AP2D was applied to exhaustive search. The image quality was not altered by this approach while the compression ratio was slightly enhanced. La compression fractale d’images permet un décodage rapide et une indépendance de la résolution mais souffre d’une lenteur dans le codage. Le présent travail présente une approche visant à réduire le temps de calcul en utilisant deux dictionnaires et une approximation de l’image en deux étapes (AP2D). L’approche AP2D peut être appliquée aux méthodes de classification ou aux méthodes de réduction du cardinal du dictionnaire et ainsi réduire davantage le temps de codage. Les résultats expérimentaux ont montré que AP2D appliquée à une recherche exhaustive a atteint un gain de temps de plus de 72%. De même AP2D appliquée à la classification de Fisher a permis une réduction de temps de codage de plus de 65%. La qualité de l’image n’a pas été altérée par cette approche et le taux de compression a légèrement augmenté.

Sign in / Sign up

Export Citation Format

Share Document