Interactive Digital Image Processing (DIP) Web Application

A comprehensive, interactive web application built with Python and Streamlit that allows users to upload images and apply a wide array of Digital Image Processing (DIP) techniques in real-time through an intuitive, user-friendly dashboard.

Key Features & Modules Implemented:

Image Operations: Core pixel-level manipulations including Addition, Subtraction, Complement, and Channel Swapping.

Image Restoration: Simulating and filtering out noise types such as Salt & Pepper and Gaussian noise.

Advanced Filters: Implementation of spatial domain filters including Average, Gaussian, Median, Laplacian, and Max/Min filters.

Histogram Processing: Grayscale conversion, Histogram Equalization, and Contrast Stretching for image enhancement.

Image Segmentation: Image binarization using Global, Otsu’s, and Adaptive Thresholding methods.

Edge Detection: Extracting structural boundaries using Sobel X & Y operators (Combined).

Morphological Operations: Shape-based processing featuring Dilation, Erosion, Boundary extraction, and Morphological Gradient