Dictionary learning (also known as sparse coding) is a representation learning technique that tries to find a sparse representation of the input data as a (sparse) linear combination of basis elements (known as atoms) that construct an over-complete spanning set (known as a dictionary). The mammalian primary visual cortex also works in the same way by exploiting the redundancy and flexibility of this type of representation. In image processing, dictionary learning has been applied on the image patches and it has shown promising results in different image processing problems such as image inpainting, image completion, and denoising. In this recipe, you will learn how to use dictionary learning for image denoising.
Python Image Processing Cookbook
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Python Image Processing Cookbook
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Overview of this book
With the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing.
With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems.
By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively.
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Current Title:
Python Image Processing Cookbook
Table of Contents (11 chapters)
Preface
Image Manipulation and Transformation
Free Chapter
Image Enhancement
Image Restoration
Binary Image Processing
Image Registration
Image Segmentation
Image Classification
Object Detection in Images
Face Recognition, Image Captioning, and More
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