A robust and fast approach for multiple image components stitching

Mustafa Jaber; Eli Saber; Mark Shaw; Jim Hewitt

doi:10.1117/12.839098

8 February 2010 A robust and fast approach for multiple image components stitching

Mustafa Jaber, Eli Saber, Mark Shaw, Jim Hewitt

Proceedings Volume 7532, Image Processing: Algorithms and Systems VIII; 753209 (2010) https://doi.org/10.1117/12.839098
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

In this paper, we present an algorithm for image stitching that avoids performance hindrance and memory issues in diverse image processing applications/ environments. High-resolution images could be cut into smaller pieces by various applications for ease of processing, especially if they are sent over a computer network. Image pieces (from several highresolution images) could be stored as a single image-set with no information about the original images. We propose a robust stitching methodology to reconstruct the original high-resolution image(s) from a target image-set that contains components of various sizes and resolutions. The proposed algorithm consists of three major modules. The first step sorts image pieces into different planes according to their spatial position, size, and resolution. It avoids sorting overlapped pieces of the same resolution in the same plane. The second module sorts the pieces from different planes according to their content by minimizing a cost function based on Mean Absolute Difference (MAD). The third module relates neighboring pieces and determines output images. The proposed algorithm could be used at a pre-processing stage in applications such as rendering, enhancement, retrieval etc, as these cannot be carried out without access to original images as individual whole components.

Citation Download Citation

Mustafa Jaber, Eli Saber, Mark Shaw, and Jim Hewitt "A robust and fast approach for multiple image components stitching", Proc. SPIE 7532, Image Processing: Algorithms and Systems VIII, 753209 (8 February 2010); https://doi.org/10.1117/12.839098

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KEYWORDS

Image resolution

Image processing

Detection and tracking algorithms

Algorithm development

Spatial resolution

Image compression

Reconstruction algorithms

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