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

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.

2010 ◽  
Vol 36 (5) ◽  
pp. 650-654 ◽  
Author(s):  
Chao SUN ◽  
Shou-Da JIANG ◽  
Jian-Feng WANG

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

2015 ◽  
Vol 738-739 ◽  
pp. 598-601
Author(s):  
Han Yang Zhu ◽  
Xin Yu Jin ◽  
Jian Feng Shen

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.


Fractals ◽  
2009 ◽  
Vol 17 (02) ◽  
pp. 149-160 ◽  
Author(s):  
SHIGUO LIAN ◽  
XI CHEN ◽  
DENGPAN YE

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.


2021 ◽  
Author(s):  
Yueh-Shan Shih

This thesis explores the effectiveness of a novel interaction model for visualizing 3D image data. The interaction model is based on user-sketched line segments known as


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