04-12-2014, 09:26 PM
image compression using ridgelet transform matlab codes
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image compression using ridgelet transform matlab codes
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image compression using ridgelet transform matlab codes
24-03-2017, 04:04 PM
The first generation curve is defined using the ridgelet transform. This package contains the MATLAB implementation of curvelet and ridgelet, as specified in. It also includes the MATLAB program for the removal of images in the domain curvelet. The curvelet transform is a multiscale and multidirectional transformation, which allows a poorly adaptive non-adaptive representation for features and curved edges. Curve applications have accelerated growing interest in the applied mathematics, signal processing, and seismic geology community in recent years. In this article, we describe some recent applications that involve image processing, seismic data exploration, turbulent flows and compressed detection. Most natural images / signals exhibit line-like edges, that is, discontinuities through curves (called singularities of lines or curves). Although wavelet applications have become increasingly popular in scientific and engineering fields, traditional wavelets work well only to represent point singularities because they ignore the geometric properties of structures and do not exploit the regularity of edges.
Wavelet-based compression, destructorization, or structure extraction become computationally inefficient for geometric characteristics with line and surface singularities. For example, when we download compressed images or videos, we often encounter a mosaic phenomenon (ie, block artifacts along the edges of images). This mosaic phenomenon is mainly due to the low capacity of the wavelets to handle the singularities of the lines.
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