Impact of multi-scale retinex computation on performance of segmentation algorithms

Zia-ur Rahman; Daniel J. Jobson; Glenn A. Woodell; Glenn D. Hines

doi:10.1117/12.543094

15 July 2004 Impact of multi-scale retinex computation on performance of segmentation algorithms

Zia-ur Rahman, Daniel J. Jobson, Glenn A. Woodell, Glenn D. Hines

Proceedings Volume 5438, Visual Information Processing XIII; (2004) https://doi.org/10.1117/12.543094
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

Classical segmentation algorithms subdivide an image into its constituent components based upon some metric that defines commonality between pixels. Often, these metrics incorporate some measure of "activity" in the scene, e.g. the amount of detail that is in a region. The Multiscale Retinex with Color Restoration (MSRCR) is a general purpose, non-linear image enhancement algorithm that significantly affects the brightness, contrast and sharpness within an image. In this paper, we will analyze the impact the (MSRCR) has on segmentation results and performance.

Citation Download Citation

Zia-ur Rahman, Daniel J. Jobson, Glenn A. Woodell, and Glenn D. Hines "Impact of multi-scale retinex computation on performance of segmentation algorithms", Proc. SPIE 5438, Visual Information Processing XIII, (15 July 2004); https://doi.org/10.1117/12.543094

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