Hands-On Image Processing with Python: Expert techniques for advanced image analysis and effective interpretation of image data

• Practical coverage of every image processing task with popular Python libraries
• Includes topics such as pseudo-coloring, noise smoothing, computing image descriptors
• Covers popular machine learning and deep learning techniques for complex image processing tasks

• Perform basic data pre-processing tasks such as image denoising and spatial filtering in Python
• Implement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in Python
• Do morphological image processing and segment images with different algorithms
• Learn techniques to extract features from images and match images
• Write Python code to implement supervised / unsupervised machine learning algorithms for image processing
• Use deep learning models for image classification, segmentation, object detection and style transfer

This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.