The Pocket Handbook of Imaging Processing Algorithms in C
This handy desktop reference gathers together into one easy-to-use volume the most popular image processing algorithms. Designed to be used at the computer terminal, it features an illustrated, annotated dictionary format — with clear, concise definitions, examples, and C program code. Covers algorithms for adaptive filters, coding and compression, color image processing, histogram operations, image fundamentals, mensuration, morphological filters, nonlinear filters, segmentation, spatial filters, spatial frequency filters, storage formats, and transforms. Includes graphic oriented techniques such as warping, morphing, zooming, and dithering. Provides algorithms for image noise generation. MARKETS: For users and developers of image processing systems and programs.
Why Read This Book
You will get a portable, terminal-friendly collection of common image-processing algorithms with ready-to-run C code so you can prototype and adapt techniques quickly. The book is a practical cookbook-style reference rather than a theory text, ideal when you need concrete implementations of filters, transforms, morphology, segmentation, and simple compression routines.
Who Will Benefit
Engineers and developers who need working C implementations of classic image-processing algorithms to integrate, test, or prototype image pipelines.
Level: Intermediate — Prerequisites: Working knowledge of C (ANSI C), basic familiarity with digital signal and image concepts (sampling, convolution, basic linear algebra).
Key Takeaways
- Implement common spatial linear filters (box, Gaussian, high/low-pass) in C for image smoothing and sharpening.
- Implement nonlinear and morphological operators (median, erosion, dilation, opening/closing) to handle noise and shape analysis.
- Apply frequency-domain transforms (FFT/DCT variants) for filtering and basic spectral operations on images.
- Perform histogram operations and basic segmentation/edge detection techniques to preprocess and analyze images.
- Implement simple coding/compression and common bitmap storage formats so you can read/write and compress images.
- Integrate small, tested C routines into larger image-processing or DSP projects for rapid prototyping.
Topics Covered
- Introduction and usage notes (terminal-friendly examples)
- Image fundamentals and storage formats (BMP, PGM, raw)
- Spatial filters: linear convolution, smoothing, sharpening
- Nonlinear filters: median and rank-order filters
- Adaptive filters and noise reduction
- Morphological operations: erosion, dilation, opening, closing
- Histogram operations and contrast enhancement
- Edge detection and segmentation basics
- Spatial-frequency methods: FFT and DCT applications
- Coding and compression: simple schemes and storage considerations
- Color image processing and color-space handling
- Geometric transforms: zooming, warping, morphing
- Noise generation and test-image utilities
- Appendix: C code listings and implementation notes
Languages, Platforms & Tools
How It Compares
Compared with Gonzalez & Woods' Digital Image Processing, this book is far more of a compact C cookbook (practical implementations) while offering less mathematical depth and theory.
