ABSTRACT

Didactic, archival, retrieval, and analysis applications in digital microscopy demand representation of color images of the same quality, either of microscope images or of their photographic reproduction. Moreover, textures in microscope images are colored textures. They may have either the same colors and different structural patterns, or different colors in the same structural patterns, or different colors and different structural patterns. Therefore, the texture description of an image should include both color and structural aspects.L2

A major problem is to reduce the transmission and the processing time and the memory required to store the digital color images, which are usually 1000 x 1000 x 24 bits (3 Mbytes), still maintaining a high information content, in order to save time and memory space for successive retrieval and analysis steps. Sophisticated compression algorithms, used to encode a color image in a new format, generate a quite satisfactory image characterized by a compression ratio (i.e., the ratio between the numbers of bytes of the original image and that of the final images), of about 30 (100 Kbytes). Dithering algorithms can be applied after compression algorithms as post processing techniques to improve overall image quality. Many compression algorithms are available; one of the most commonly used is JPEG.3 With this algorithm, no differences are detectable between the original and the compressed image, at least at preliminary visual inspection. However, by analyzing the scene of the JPEG compressed color image, with algorithms that perform the partition between the background and the objects (segmentation) and/or extract features, one may notice that JPEG compression heavily modifies image frequencies, introduces new textures, and does not decrease the processing time. Different compression algorithms (e.g., those developed by the authors), based

on the reduction of the number of colors to a characteristic set (i.e., the smallest number of colors satisfying some criteria or features), could be used to improve image clarity and decrease processing time. This chapter describes how to deal with the problems that can occur when working with digital microscope color images.