There has been a focus on developing image indexing techniques which have the capability to retrieve image based on their contents. The technologies are now generally referred to as Content-Based Image Retrieval (CBIR). Due to its extensive potential applications, CBIR has attracted a great amount of attention in recent years. Using colors as the content, content based image processing have been carried out for a sample of high resolution urban image and low resolution rural image scenes obtained from satellites. The color based processing has been utilized to identity important urban features such as buildings and gardens and rural features such as natural vegetation, water bodies and fields applying various techniques. The techniques included color based extractions using neighborhood rules and histograms. An estimation of the features and available resources from the imageries have been made using the color spectral graphs. The results of the analysis are presented and discussed in the paper.

There has been a focus on developing image indexing techniques which have the capability to retrieve image based on their contents. The main feature extraction methods are content Based Image Retrieval (CBIR) also known as query by Image content (QBIC). This paper presents a technique to derive the colors, shapes, textures, or any other information that can be derived from a satellite image Using Texture filters and realizing it with artificial neural networks. This image processing technique are been utilized to identify important urban features such as buildings and gardens and rural features such as natural vegetation, water bodies, and fields. Textures are represented by Texel, which are then placed into a number of sets, depending on how many textures are detected in the image.