A deep image coding scheme with generative network to learn from correlated images.

2021 ◽  
pp. 1-1
Author(s):  
Yihao Chen ◽  
Bin Tan ◽  
Jun Wu ◽  
Zhifeng Zhang ◽  
Haoqi Ren
Keyword(s):  
Image Coding ◽  
Coding Scheme ◽  
Deep Image

SECURE FRACTAL IMAGE CODING BASED ON FRACTAL PARAMETER ENCRYPTION

Fractals ◽  
2009 ◽  
Vol 17 (02) ◽  
pp. 149-160 ◽  
Author(s):  
SHIGUO LIAN ◽  
XI CHEN ◽  
DENGPAN YE
Keyword(s):  
Image Coding ◽  
Parameter Distribution ◽  
Self Similarity ◽  
Image Encoding ◽  
Coding Scheme ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Fractal Parameters ◽  
Fractal Encoding ◽  
Computational Resources

In recent work, various fractal image coding methods are reported, which adopt the self-similarity of images to compress the size of images. However, till now, no solutions for the security of fractal encoded images have been provided. In this paper, a secure fractal image coding scheme is proposed and evaluated, which encrypts some of the fractal parameters during fractal encoding, and thus, produces the encrypted and encoded image. The encrypted image can only be recovered by the correct key. To maintain security and efficiency, only the suitable parameters are selected and encrypted through investigating the properties of various fractal parameters, including parameter space, parameter distribution and parameter sensitivity. The encryption process does not change the file format, keeps secure in perception, and costs little time or computational resources. These properties make it suitable for secure image encoding or transmission.

Efficient hybrid image coding scheme for color facsimile

1996 ◽  
Vol 79 (9) ◽  
pp. 51-61
Author(s):  
Satoshi Katsuno ◽  
Atsushi Koike ◽  
Yoshinori Hatori ◽  
Toshiaki Endoh
Keyword(s):  
Image Coding ◽  
Coding Scheme

Two Channel Image Coding Scheme

1989 ◽  
Author(s):  
Diego P. de Garrido ◽  
Paulo Roberto R. L. Nunes ◽  
Jacques Szczupak
Keyword(s):  
Image Coding ◽  
Coding Scheme ◽  
Channel Image

scholarly journals Autofocus on Depth of Interest for 3D Image Coding

2017 ◽  
Vol 2017 ◽  
pp. 1-15
Author(s):  
Khouloud Samrouth ◽  
Olivier Deforges ◽  
Yi Liu ◽  
Mohamad Khalil ◽  
Wassim EL Falou
Keyword(s):  
Image Coding ◽  
Region Of Interest ◽  
Depth Map ◽  
3D Image ◽  
Coding Scheme ◽  
Analysis Process ◽  
Adaptive Resolution ◽  
Local Quality ◽  
Extraction Scheme ◽  
3D Sequence

For some 3D applications, one may want to focus on a specific depth zone representing a region of interest in the scene. In this context, we introduce a new functionality called “autofocus” for 3D image coding, exploiting the depth map as an additional semantic information provided by the 3D sequence. The method is based on a joint “Depth of Interest” (DoI) extraction and coding scheme. First, the DoI extraction scheme consists of a precise extraction of objects located within a DoI zone, given by the viewer or deduced from an analysis process. Then, the DoI coding scheme provides a higher quality for the objects in the DoI at the expense of other depth zones. The local quality enhancement supports both higher SNR and finer resolution. The proposed scheme embeds the Locally Adaptive Resolution (LAR) codec, initially designed for 2D images. The proposed DoI scheme is developed without modifying the global coder framework, and the DoI mask is not transmitted, but it is deduced at the decoder. Results showed that our proposed joint DoI extraction and coding scheme provide a high correlation between texture objects and depth. This consistency avoids the distortion along objects contours in depth maps and those of texture images and synthesized views.

scholarly journals Multiple Description Wavelet-Based Image Coding Using Iterated Function System

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jie Yang
Keyword(s):  
Image Coding ◽  
Recent Literature ◽  
Iterated Function System ◽  
Wavelet Coefficient ◽  
Function System ◽  
Packet Losses ◽  
Multiple Description ◽  
Coding Scheme ◽  
Iterated Function ◽  
Description Coding

Recent literature highlights the multiple description coding (MDC) as a promising method to solve the problem of resilient image coding over error-prone networks, where packet losses occur. In this paper, we introduce a novel multiple description wavelet-based image coding scheme using fractal. This scheme exploits the fractal’s ability, which is to describe the different resolution scale similarity (redundancy) among wavelet coefficient blocks. When one description is lost, the lost information can be reconstructed by the proposed iterated function system (IFS) recovering scheme with the similarity and some introduced information. Compared with the referenced methods, the experimental results suggest that the proposed scheme can achieve better performance. Furthermore, it is substantiated to be more robust for images transmission and better subjective quality in reconstructed images even with high packet loss ratios.

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