Color image compression is the process of reducing the size of a color image file while maintaining acceptable visual quality. Since color images contain more data than grayscale images, compression plays a critical role in reducing storage and transmission costs. Various mathematical techniques are used to eliminate redundancy in color images, enabling efficient storage and … Read more
Noise in color images refers to unwanted random variations in color and brightness values that distort the quality of the image. It can arise from multiple sources during image acquisition, processing, transmission, or storage. The presence of noise can significantly reduce the clarity and visual appeal of images, making it essential to understand how it … Read more
Image segmentation is a fundamental task in image processing and computer vision, where the goal is to partition an image into multiple segments or regions. Each segment typically corresponds to different objects or parts of the scene. Color-based segmentation is one of the most popular approaches to segment an image, especially when color information is … Read more
In image processing, smoothing and sharpening are fundamental techniques used to either reduce noise (smoothing) or enhance edges and fine details (sharpening). These processes are particularly useful when dealing with both grayscale and color images. In this article, we will focus on the mathematical concepts behind color image smoothing, as outlined in the image provided, … Read more
Color transformations involve processing the components of a color image within a single color model, rather than converting between different models. In these transformations, each pixel of the color image is represented as a triplet (for RGB or HSI) or quartet (for CMYK) of values corresponding to the chosen color space. Formulation of Color Transformations … Read more
Full-color image processing involves handling and manipulating images that consist of multiple color channels. These channels, typically Red, Green, and Blue (RGB), define the color of each pixel in the image. This method is essential in areas like photography, medical imaging, and computer vision, where accurate color representation and manipulation are crucial for analysis. In … Read more
Pseudocolor (or false color) image processing is a technique where colors are assigned to grayscale values in a monochrome image based on a specified criterion. Unlike true color images, where colors represent actual spectral information, pseudocolor assigns artificial colors to enhance the visual interpretation of grayscale images. This process is particularly useful in scientific and … Read more
A color model, also called a color space or color system, is designed to provide a standardized method for specifying colors. This is essential for ensuring consistency and accuracy across various platforms and applications. In essence, a color model defines a coordinate system and a subspace within that system, where a unique point represents each … Read more
The human brain’s perception and interpretation of color is a complex physiopsychological process that is not fully understood. However, the physical nature of color can be described scientifically, supported by both experimental findings and theoretical principles. Sir Isaac Newton, in 1666, discovered that when sunlight passes through a glass prism, it separates into a continuous … Read more
In the field of medical imaging, the process of reconstructing images from projections plays a crucial role, particularly in technologies such as CT scans. This process, often referred to as back-projection, involves the transformation of 1D absorption data into 2D images. The figures provided illustrate the principles behind back-projection, starting with a simple object (like … Read more
