Papers

Title: Multicamera Image Vision with Quality Measure
Year of Publication: 2017
Publisher: International Journal of Computer Systems (IJCS)
ISSN: 2394-1065
Series: Volume 04, Number 3, March 2017
Authors:Jayashri R.Gangurde, Mayur Rathi

Citation:

Jayashri R.Gangurde, Mayur Rathi, "Multicamera Image Vision with Quality Measure", In International Journal of Computer Systems (IJCS), pp: 50-54, Volume 4, Issue 3, March 2017. BibTeX

@article{key:article,
	author = {Jayashri R.Gangurde,  Mayur Rathi},
	title = {Multicamera Image Vision with Quality Measure},
	journal = {International Journal of Computer Systems (IJCS)},
	year = {2017},
	volume = {4},
	number = {3},
	pages = {50-54},
	month = {March}
	}


Abstract

With the increasing demand of multiview application, quality related issues of multicamera images and videos is now crucial to the building of such applications. Quality of images are depending upon number of factors, which may be configuration of various cameras, stability of camera during taking photo, and the calibration process etc. In the projected literature survey there are various quality assessment methods are developed for images & videos taken from single camera but no more development in multi camera quality assessment. With this intention we develop some objective standard for multi camera system. We recognized that there are two types of distortions exist in multi camera images that are geometric and photometric. To find perceived quality of separate camera image comparable distortion plays very important role. These distortions are converted into components such as luminance, Contrast, edge arrangement & spatial motion. For these components we suggest various algorithms that calculate such components. Multicamera image Vision with quality measure (MIVQM) is calculated by combining three indices which are luminance and contrast, spatial motion and edge based arrangement. The result and comparison with the other measures, like Peak Signal-to Noise Ratio (PSNR), Mean Structural Similarity (SSIM), and Visual Information Fidelity (VIF) prove that MIVQM surpass other measure to capture the quality of images from multicamera system. And in last, outcomes vs. subjective assessments are verified.

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Keywords

Fidelity Measure, qualitative assessment of images, multicamera image arrays, perceptible quality.