PixelView

Overview

Image processing algorithms
made accessible

PixelView is a desktop application that brings scientific image processing algorithms out of textbooks and into a usable tool. Load any image, select an algorithm from the menu, and see the result immediately - no coding required, no command-line arguments to remember.

The tool includes implementations of classic image processing operations (edge detection, thresholding, histogram equalization) alongside machine learning algorithms for classification and segmentation. It serves as both a practical tool and a learning aid for understanding how these algorithms transform pixel data.

Technical

From pixels to understanding

Built in Python, PixelView leverages NumPy for efficient array operations on image data, with algorithm implementations that operate directly on pixel matrices. The GUI provides immediate visual feedback - select an algorithm, adjust parameters, and watch the output image update.

The tool runs cross-platform on macOS and Linux, adapting its interface to each platform's windowing system. Algorithms are modular - each is a self-contained function that takes an image array and returns a transformed array, making it straightforward to add new operations.

Algorithms

A toolkit of classic techniques

Edge detection (Sobel, Canny), morphological operations (erosion, dilation), color space transformations, histogram analysis, thresholding methods, and spatial filtering. On the ML side: k-means clustering for segmentation, principal component analysis for dimensionality reduction, and classification algorithms for pattern recognition in image data.