Wavelet Based Image Segmentation

Segment image containing blobs of various intensities and shapes in noisy inhomogenous background

This code is a part of our work "Nonseparable Wavelet Based Segmentation ..." . It contains the methods to extract out the darker or lighter blobs (spots) of various intensities and shapes (including faint/ low intensity spots) from noisy or inhomogeneous background. The method is designed for segmenting the protein blobs from 2D gel images. The other suitable images are quantum dot images, images of cirucular objects in noisy inhomogneous background, malaria parasite images, oil blobs on sea/river, fluroscence cell images similar to http://www.robots.ox.ac.uk/~vgg/research/counting/, dermoscopy images etc. The kernel-bandwidth and contrast threshold are two parameter that may need to change according to the image. For 2D gel images, you may vary only contrast threshold for your dataset although no change is required in any parameter in case of 2D gel images. The little modification in region refinement part according to an application may segment many other type of images such as some type of microarray images.