Image Processing and Acquisition Using Python

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing--one of the first books to integrate these topics together. By improving readers' knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples.

A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The second part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry.

Features

• Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images.
• Contains many examples, detailed derivations, and working Python examples of the techniques.
• Offers practical tips on image acquisition and processing.
• Includes numerous exercises to test the reader's skills in Python programming and image processing, with solutions to selected problems, example programs, and images available on the book's web page.

New to this edition

• Machine learning has become an indispensable part of image processing and computer vision, so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks.
• A new chapter on affine transform and many new algorithms.
• Updated Python code aligned to the latest version of modules.

《使用Python進行影像處理與擷取》為讀者提供了影像擷取和影像處理的基礎知識，是首本將這兩個主題整合在一起的書籍之一。通過提升讀者對影像擷取技術和相應影像處理方法的了解，本書將幫助讀者更有效和節省成本地進行實驗，並進行更準確的分析和測量。Python一直被認為是非程式設計師最容易學習的語言之一，本書使用了多個實際例子來講解。

本書的第一部分是為有經驗讀者提供的複習，介紹了Python、Python模組、使用Python讀寫影像以及影像基礎知識。第二部分討論了影像處理的基礎知識，包括使用濾波器進行前/後處理、分割、形態學操作和測量。第二部分描述了使用不同模式進行影像擷取的方法，例如X射線、CT、MRI、光學顯微鏡和電子顯微鏡。這些模式涵蓋了目前學術界和工業界研究人員常用的大部分影像擷取方法。

特點：

- 同時涵蓋了獲取影像的物理方法和理解影像背後科學所需的分析處理方法。
- 包含許多例子、詳細的推導和使用Python的實際技巧。
- 提供有關影像擷取和處理的實用提示。
- 包含大量練習，以測試讀者在Python編程和影像處理方面的技能，並提供選定問題的解決方案、示例程式和圖像，這些資源可在書籍的網頁上獲得。

本版新增內容：

- 機器學習已成為影像處理和計算機視覺不可或缺的一部分，因此在這個新版中新增了兩個章節：一個是關於神經網絡，另一個是關於卷積神經網絡。
- 新增了一個關於仿射變換的章節和許多新的演算法。
- 更新了與最新版本模組相符的Python程式碼。

Ravishankar Chityala, Ph.D. is Principal Engineer at IonPath, with eighteen years of experience in image processing. He teaches Python programming and Deep learning using Tensorow at the University of California Santa Cruz, Silicon Valley Campus. Previously, he worked as an image processing consultant at the Minnesota Supercomputing Institute of the University of Minnesota. As an image processing consultant, Dr. Chityala had worked with faculty, students and staff from various departments in the scientific, engineering and medical fields at the University of Minnesota, and his interaction with students had made him aware of their need for greater understanding of and ability to work with image processing and acquisition. Dr. Chityala co-authored Essential Python (Essential Education, California, 2018), also contributed to the writing of Handbook of Physics in Medicine and Biology(CRC Press, Boca Raton, 2009, Robert Splinter). His research interests include image processing, machine learning and deep learning.

Sridevi Pudipeddi, Ph.D. has eleven years of experience teaching undergraduate courses. She teaches Machine Learning with Python and Python for Data Analysis at the University of California Berkeley at San Francisco campus. Dr. Pudipeddi's research interests are in machine learning, applied mathematics and image and text processing. Python's simple syntax and its vast image processing capabilities, along with the need to understand and quantify important experimental information through image acquisition, have inspired her to co-author this book. Dr. Pudipeddi co authored Essential Python (Essential Education, California, 2018).

Ravishankar Chityala博士是IonPath的首席工程師，擁有十八年的影像處理經驗。他在加州大學聖塔克魯茲分校矽谷校區教授Python程式設計和使用TensorFlow進行深度學習。之前，他曾在明尼蘇達大學明尼蘇達超級計算機研究所擔任影像處理顧問。作為一名影像處理顧問，Chityala博士曾與明尼蘇達大學的科學、工程和醫學領域的教職員工以及學生合作，他與學生的互動使他意識到他們對影像處理和獲取的理解和能力的需求。Chityala博士是Essential Education出版的《Essential Python》（加利福尼亞州，2018年）的合著者，也曾為《物理醫學和生物學手冊》（CRC Press，Boca Raton，2009年，Robert Splinter）的撰寫做出貢獻。他的研究興趣包括影像處理、機器學習和深度學習。

Sridevi Pudipeddi博士在教授本科課程方面擁有十一年的經驗。她在加州大學舊金山分校伯克利校區教授Python的機器學習和數據分析。Pudipeddi博士的研究興趣包括機器學習、應用數學以及影像和文本處理。Python簡潔的語法和其廣泛的影像處理能力，以及通過影像獲取來理解和量化重要的實驗信息的需求，激發了她合著這本書的靈感。Pudipeddi博士是Essential Education出版的《Essential Python》（加利福尼亞州，2018年）的合著者。