Finding a Needle in a Haystack: An Image Processing Approach

Abstract

Image segmentation (also known as object/edge detection) is the process of dividing an image into its constituent parts using information about the boundaries between objects, edges within objects, variations in intensity, et cetera. Often, the human eye can easily recognize salient information from an image; however, background variations in intensity, noise and other degradations, and other highly oscillatory features make the process of image segmentation challenging. This work is unique because we propose using a cartoon-texture-noise separation to remove highly oscillatory features from the image prior to segmentation. The cartoon and texture components can be used to analyze important information from the original image; specifically, by applying a segmentation algorithm on the cartoon component, we can extract objects from the original image. A new numerical implementation is provided for one of the two decompositions used as well as various experimental results. The method is applied to the classic example of finding a needle in a haystack, as well as real images where the texture component and noise causes problems for standard techniques. 1