Hierarchical Image Segmentation Based on Wavelet Transforms

A the field of digital image processing refers to processing digital images by means of a digital computer. Note that a digital image is composed of a finite number of elements, each of which has a particular location and value. These elements are referred to as picture elements, image elements, pels and pixels. Pixel is the term most widely used to denote the elements of a digital image. There are no clear cut boundaries in the continuum from image processing at one end to computer vision at the other. However, one useful paradigm is to consider three types of computerized processes in this continuum: low-level, mid-level and high-level processes. Low level processing involves primitive operations such as image preprocessing to reduce noise, contrast enhancement and image sharpening. A low level processing is characterized by the fact that both its inputs and outputs are images. Mid- level processing on images involves tasks such as segmentation, description of those objects and classification of those objects. In this paper a novel segmentation method based on wavelet transforms is proposed. . This method is more efficient for a wide range of contour features such as junctions, corners and ridges, especially at low bit rates.