Author: Ramona Zaharia
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Adaptive Compression Algorithm for Full Colour Three Dimensional Integral Images
Author: Ramona Zaharia
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Adaptive Source Models for Reversible Compression of Digitized Images
Author: Keshi Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 224
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 224
Book Description
Adaptive Compression of Images Using High-order Entropy Coding
Author: Steve Shu Yu
Publisher:
ISBN:
Category :
Languages : en
Pages : 278
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 278
Book Description
Adaptive Compression of Images
Author: George Zweig
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
Book Description
We propose an adaptive compression enhancement scheme for images, that faithfully preserves edges that exist at certain scales. The image gradient is decomposed in a wavelet basis to locate edges at specific scales. Based on their location, the corresponding wavelet coefficients in the wavelet decomposition of the image are earmarked for preservation. A scale-space localized implementation of the gradient operator is derived in the wavelet transform domain, based on the Lemarie-Rieusset diagonalization of the derivative operator for functions of one variable. By decomposing an image with respect to a standard biorthogonal wavelet basis, we succeed in obtaining the gradient (edge) information in the image (with respect to associated hybrid biorthogonal wavelet bases) at certain desired scales only. There are several advantages to and applications of such a localized implementation of the gradient, apart from its computational efficiency. Adaptive compression of images based on edge-strengths at specific scales becomes possible, so that compression can be less in the neighborhood of edges at those scales at which its characteristics are best represented. Such preferential compression capability is useful for the compression of vast databases of oceanographic and astronomical images; faint edges characterizing interfaces between warm and cold ocean currents in satellite oceanographic images, and boundaries between interstellar dust and nebulae of subtly varying luminosities in astronomical images are important image features that need to be preserved with minimum distortion, while achieving significant compression in other parts of these images that correspond to known features such as land-ocean boundaries or familiar stars.
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
Book Description
We propose an adaptive compression enhancement scheme for images, that faithfully preserves edges that exist at certain scales. The image gradient is decomposed in a wavelet basis to locate edges at specific scales. Based on their location, the corresponding wavelet coefficients in the wavelet decomposition of the image are earmarked for preservation. A scale-space localized implementation of the gradient operator is derived in the wavelet transform domain, based on the Lemarie-Rieusset diagonalization of the derivative operator for functions of one variable. By decomposing an image with respect to a standard biorthogonal wavelet basis, we succeed in obtaining the gradient (edge) information in the image (with respect to associated hybrid biorthogonal wavelet bases) at certain desired scales only. There are several advantages to and applications of such a localized implementation of the gradient, apart from its computational efficiency. Adaptive compression of images based on edge-strengths at specific scales becomes possible, so that compression can be less in the neighborhood of edges at those scales at which its characteristics are best represented. Such preferential compression capability is useful for the compression of vast databases of oceanographic and astronomical images; faint edges characterizing interfaces between warm and cold ocean currents in satellite oceanographic images, and boundaries between interstellar dust and nebulae of subtly varying luminosities in astronomical images are important image features that need to be preserved with minimum distortion, while achieving significant compression in other parts of these images that correspond to known features such as land-ocean boundaries or familiar stars.
Adaptive-model Predictive Lossless Compression of Medical Images
Author: Akmal A. Younis
Publisher:
ISBN:
Category : Diagnostic imaging
Languages : en
Pages : 208
Book Description
Publisher:
ISBN:
Category : Diagnostic imaging
Languages : en
Pages : 208
Book Description
Intelligent Fractal-Based Image Analysis
Author: Soumya Ranjan Nayak
Publisher: Elsevier
ISBN: 0443184690
Category : Computers
Languages : en
Pages : 320
Book Description
Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis. Intelligent Fractal-Based Image Analysis: Application in Pattern Recognition and Machine Vision provides insights into the current strengths and weaknesses of different applications as well as research findings on fractal graphics in engineering and science applications. The book aims to improve the exchange of ideas and coherence between various core computing methods and highlight the relevance of related application areas for advanced as well as novice-user application. The book presents an in-depth look at core concepts, methodological aspects, and advanced feature opportunities, focusing on major real time applications in engineering science and health science. The book will appeal to researchers, data scientists, industry professionals, and graduate students in the fields of fractal graphics and its related applications. - Investigates advanced fractal theories spanning neural networks, fuzzy logic, machine learning, deep learning, and hybrid intelligent systems in solving pattern recognition problems - Explores the application of fractal theories to a wide range of medical image processing modalities - Presents case studies that illustrate the application and integration of fractal theories into intelligent computing in the resolution of important pattern recognition and machine vision problems
Publisher: Elsevier
ISBN: 0443184690
Category : Computers
Languages : en
Pages : 320
Book Description
Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis. Intelligent Fractal-Based Image Analysis: Application in Pattern Recognition and Machine Vision provides insights into the current strengths and weaknesses of different applications as well as research findings on fractal graphics in engineering and science applications. The book aims to improve the exchange of ideas and coherence between various core computing methods and highlight the relevance of related application areas for advanced as well as novice-user application. The book presents an in-depth look at core concepts, methodological aspects, and advanced feature opportunities, focusing on major real time applications in engineering science and health science. The book will appeal to researchers, data scientists, industry professionals, and graduate students in the fields of fractal graphics and its related applications. - Investigates advanced fractal theories spanning neural networks, fuzzy logic, machine learning, deep learning, and hybrid intelligent systems in solving pattern recognition problems - Explores the application of fractal theories to a wide range of medical image processing modalities - Presents case studies that illustrate the application and integration of fractal theories into intelligent computing in the resolution of important pattern recognition and machine vision problems
Adaptive Block-size Transform Coding for Image Compression
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Compression of Medical Images Using an Adaptive Vector Quantization Algorithm
Author: Kraig L. Anderson
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 144
Book Description
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 144
Book Description
DCT Image Compression with Adaptive Block-size Segmentation
Author: Chou Hong Hong
Publisher:
ISBN:
Category :
Languages : en
Pages : 102
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 102
Book Description
Scene Adaptive Image Sequence Compression
Author: Jungwoo Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 300
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 300
Book Description