Concise Introduction to Image Processing using C++

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A01=Choi-Hong Lai
A01=Meiqing Wang
advanced image analysis techniques
Author_Choi-Hong Lai
Author_Meiqing Wang
binary
Binary Image
Bmp Format
Category=UMX
Colour Triangle
Convolution Kernel
Crack Edges
DFT
Edge Confidence
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
fractal compression
function
Gabor Transform
grey
Grey Level
Grey Scale Image
High Pass Filtering Method
Hough Transform
image denoising
mathematical modeling
Mathematical Morphology
Median Filtering Method
Nonlinear Diffusion Model
object detection
operator
original
Original Lena Image
partial differential equations
pixel
Pixel Point
point
Point Spread Function
prewitt
Range Blocks
Raw Format
RGB Colour Model
RGB Model
RGB Space
scale
Source Symbol
spread
Vice Versa
wavelet transform

Product details

  • ISBN 9781584888970
  • Weight: 544g
  • Dimensions: 156 x 234mm
  • Publication Date: 20 Nov 2008
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, allowing you to easily apply these techniques in real-world problems.

The book presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations (PDEs), and new image compression methods, such as fractal image compression and wavelet compression. It begins with coverage of representation, and then moves on to communications and processing. It concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. The accompanying downloadable resources contain code for all algorithms.

Suitable as a text for any course on image processing, the book can also be used as a self-study resource for researchers who need a concise and clear view of current image processing methods and coding examples. The authors introduce mathematical concepts with rigor suitable for readers with some background in calculus, algebra, geometry, and PDEs. All algorithms described are illustrated with code implementation and many images compare the results of different methods. The inclusion of C++ implementation code for each algorithm described enables students and practitioners to build up their own analysis tool.

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