Comprehensive Digital Image Collection for Image Processing
A comprehensive collection of digital images for image processing, including various file formats and sizes, suitable for testing different algorithms and techniques.
Block Coding for Digital Image Processing with MATLAB Enhancements
Implementation of digital image processing techniques in MATLAB including block coding, digitization, sharpening, gray-level transformation, histogram equalization, and other fundamental operations with code integration and algorithm explanations.
Digital Image Processing Series Programs
This series provides implementation code with detailed explanations for various digital image processing techniques: P0301: Displaying digital image matrix data and performing Fourier transforms using MATLAB's fft2 function P0302: Image compression through 2D Discrete Cosine Transform (DCT) implementation P0303: Contrast enhancement using grayscale transformation methods with intensity mapping P0304: Histogram equalization algorithm for image enhancement P0305: Simulating image degradation with Gaussian white noise and salt-and-pepper noise using imnoise function P0306: Filtering salt-and-pepper noise using 2D median filtering function medfilt2 P0307: Mean filtering of noisy images using MATLAB's filter2 function with averaging kernels P0308: Adaptive Wiener filtering for image restoration P0309: Image sharpening using five different gradient enhancement methods including Sobel and Prewitt operators P0310: High-pass filtering and mask processing techniques
MATLAB Implementation of Sobel Operator for Digital Image Processing
MATLAB program for Sobel operator edge detection algorithm with implementation details
Digital Image Processing: Image Translation and Transformation
This program implements image translation, rotation, and other transformations in digital image processing using MATLAB, featuring comprehensive image manipulation capabilities with optimized algorithmic implementations.
Threshold Segmentation and Morphological Processing in Digital Image Processing
Digital Image Processing: Threshold Segmentation and Morphological Processing - This program effectively achieves graphic extraction through comprehensive implementation, including complete code, detailed algorithm explanations, and runtime results demonstration.
Functional Interface Design for Digital Image Processing
MATLAB-based GUI design for digital image processing with modular functionality implementation
Answer Sheet Recognition System Based on MATLAB [GUI Interface + Thesis]
The research content of this project includes: (1) Designing the overall architecture of the answer sheet recognition system, including system framework, hardware composition, and software development plan with primary focus on software implementation. (2) Determining digital image processing algorithms involving image preprocessing, tilt and rotation correction, and binary transformation. Through comparative analysis of multiple processing methods combined with image characteristics, Hough transform was selected for detecting line inclination angles in images followed by rotational correction. (3) Implementing identification of answer-marking areas and student ID regions using MATLAB software, achieving accurate extraction of student IDs and answers (both multiple-choice and single-choice questions) through optimized region detection algorithms.
Digital Image Processing: Image Restoration Algorithms Source Code
Digital Image Processing Image Restoration Algorithms Source Code (Wiener Filter, Least Squares Method, Lucy-Richardson Algorithm) with Implementation Details
Digital Image Processing: Filtering and Fourier Compression
Digital image processing techniques for filtering and Fourier compression, including Ideal Low-Pass Filter, Butterworth High-Pass Filter, Gaussian Band-Pass Filter, Gaussian Band-Stop Filter, and FFT-based image compression. Implementation examples with comparative screenshots of original and processed images are provided.