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Proceedings ArticleDOI

Focused JPEG encoding based upon automatic preidentified regions of interest

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TLDR
A focused-procedure based upon a collection of image processing algorithms that serve to identify regions-of-interest (ROIs), over a digital image is developed, so that the JPEG version allows the result of the compression to be formatted into a file compatible for standard JPEG decoding.
Abstract
We have developed a focused-procedure based upon a collection of image processing algorithms that serve to identify regions-of-interest (ROIs), over a digital image. To loci of these ROIs are quantitatively compared with ROIs identified by human eye fixations or glimpses while subjects were looking at the same digital images. The focused- procedure is applied to adjust and adapt the compression ratio over a digital image: - high resolution and poor compression for ROIs; low resolution and strong compression for the major expanse of the entire image. In this way, an overall high compression ratio can be achieved, while at the same time preserving, important visual information within particularly relevant regions of the image. We have bundled the focused-procedures with JPEG, so that the JPEG version allows the result of the compression to be formatted into a file compatible for standard JPEG decoding. Thus, once the image has been compressed, it can be read without difficulty.

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Mesh saliency

TL;DR: This paper defines mesh saliency in a scale-dependent manner using a center-surround operator on Gaussian-weighted mean curvatures to capture what most would classify as visually interesting regions on a mesh.
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Algorithms for defining visual regions-of-interest: comparison with eye fixations

TL;DR: This paper investigates and develops a methodology that serves to automatically identify a subset of aROIs (algorithmically detected ROIs) using different image processing algorithms (IPAs), and appropriate clustering procedures, and compares hROIs with hROI as a criterion for evaluating and selecting bottom-up, context-free algorithms.
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Adaptive color image compression based on visual attention

TL;DR: This paper reports an adaptive still color image compression method which produces automatically selected ROI with a higher reconstruction quality with respect to the rest of the input image.
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Region-of-interest processing for electronic visual prostheses

TL;DR: Visual perception experiments undertaken with 192 normally sighted viewers to simulate artificially induced vision expected from emerging electronic visual prosthesis designs show that ROI processing improves scene understanding for low-quality images when used in a zoom application.
Proceedings ArticleDOI

Static image simulation of electronic visual prostheses

TL;DR: Results from testing of 174 normally sighted subjects who viewed a set of low quality (low spatial resolution and low grey-scale) static images have identified informative image processing operations which can improve understanding of picture content.
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