Source encoders, quantizers, and entropy encoders. Lossless vs. Lossy Compression:
Coding techniques where the original image can be perfectly reconstructed.
Transform coding using the Discrete Cosine Transform (DCT), which forms the foundation of the JPEG compression standard. How to Structure Your "Jayaraman DIP" Presentation Slides digital image processing jayaraman ppt
: In simple terms, an image is just a matrix of numbers. Each element in this matrix is a pixel, holding a specific value that dictates its brightness or color. Slide 3: Fundamental Steps in DIP Content : Diagram of the DIP pipeline: Image Acquisition →right arrow Enhancement →right arrow Restoration →right arrow Color Processing →right arrow →right arrow Compression →right arrow Morphological Processing →right arrow Segmentation →right arrow Object Recognition.
Medical imaging, machine vision, and industrial inspection. Source encoders, quantizers, and entropy encoders
Expanding dark pixels and compressing bright pixels (
Segmentation algorithms are generally based on one of two basic properties of intensity values: discontinuity and similarity. Detection of Discontinuities (Edge-Based) Finding abrupt changes in intensity. Transform coding using the Discrete Cosine Transform (DCT),
Automatically finding a transformation function to produce an image with a uniform histogram, improving contrast.
However, the PPTs remain relevant because:
Defining boundaries and paths between pixels to understand image topology. 3. Image Enhancement Techniques
: Representing images in various degrees of resolution, which is highly useful for data compression.