本书是取材于数字图像处理领域几十年的发展成果，包括传统的灰度图像处理和最新的彩色图像处理内容，结合多年的教学、科研和实践经验编写而成。 本书既全面介绍了数字图像处理的理论系统，又强调它的实践价值。首先介绍了隐式马尔可夫模型、预测模型、采样理论、图像变换等基本理论知识，然后逐章介绍图像的编码和文件格式，图像的增强、恢复和分割等内容，最后两章介绍了彩色图像处理的基本内容和基于内容的图像检索技术。 本书可作为高校计算机、生医工程等有关图像处理专业的高年级学生和研究生的教材或者作为从事图像处理相关领域科研人员的参考书。 -the book is drawn from the field of digital image processing decades of development gains, including traditional gray image processing and the latest color image processing, combining years of teaching, research and practical experience prepared. The book is a comprehensive introduction to digital image processing theory, emphasizing its value in practice. First on the hidden Markov model, forecasting model, sampling theory, image transform the basic theoretical knowledge, Then each chapter is devoted to image coding and file format, image enhancement, restoration and segmentation, etc., The last two chapters of color image processing and the basic elements of content-based image retrieval technology. This book as a college computer, Biomedical engineering and other professional image proc 下载
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