The FlexWave-ii has been developed as a dedicated image compression component for spaceborn applications, enabling a multitude of application scenarios, including lossless and lossy compression. The FlexWave-ii provid...
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ISBN:
(纸本)9290928174
The FlexWave-ii has been developed as a dedicated image compression component for spaceborn applications, enabling a multitude of application scenarios, including lossless and lossy compression. The FlexWave-ii provides scalable compression, allowing gradual enhancement or de gradation of the image quality in a programmable way. A wavelet-based compression scheme has been selected because of the intrinsic scalable characteristics. Moreover the compression criteria can be tuned separately for optimal measurement and visual data compression. The FlexWave-ii provides full scalability features and high processing performance. It supports push-broom imageprocessing. The wavelet transform engine is capable of computing up to 5 levels of wavelet transform with 5/3-, 9/3- or 9/7-tap wavelet filters, for image sizes as large as 1k x 1k pixels. On an FPGA implementation, clocked on 41 MHz, a processing performance of up to 10 Mpixels/second was measured. The wavelet compression engine allows two compression modes: a fixed compression ratio mode optimised for user-defined criteria and a fixed quantisation mode with user defined quantisation tables.
image compression is one of the major imageprocessing techniques that is widely used in medical, automotive, consumer and military applications. Discrete wavelet transforms is the most popular transformation techniqu...
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The wavelet transform technology is widely used in many fields, such as the graphics processing, the imageprocessing, the video-voice processing, and the digital signalprocessing, and has achieved good application r...
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ISBN:
(纸本)9783030152352;9783030152345
The wavelet transform technology is widely used in many fields, such as the graphics processing, the imageprocessing, the video-voice processing, and the digital signalprocessing, and has achieved good application results. Starting from the principles and types of the imageprocessing technology based on the wavelet transform, two processing methods of the continuous wavelet transform and the discrete wavelet transform are described in detail, and their specific applications and advantages in the image compression and the image denoising are enumerated.
The introduction of wavelets in signal and imageprocessing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and noise removal, to ...
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ISBN:
(纸本)081942840X
The introduction of wavelets in signal and imageprocessing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and noise removal, to name a few. Although wavelets are popular and used extensively in research and in engineering applications, their use in signature detection and classification is still an area open to extensive investigation. This paper discusses waveletimageprocessing working in synergy with other processing techniques to detect and recognize abnormal and cueing signatures that are important to diagnostic medicine - detection and recognition of microcalcification clusters in mammograms. In this application, an innovative detection algorithm that takes advantage of wavelet multiresolution analysis and synthesis is developed to assist radiologists looking for clusters of microcalcifications in digitized mammograms. Microcalcification regions may not be detectable by visual inspection or other detection techniques because of their inherent complexity. The algorithm presented in this paper successfully unmasks the complexity and limits the false positives. A thorough analysis, algorithm description and examples are shown in this paper.
A multiscale vision model based on a pyramidal wavelet transform is described in the present paper. The pyramidal wavelet algorithm is modified in order to satisfy a correct sampling at each scale. Objects are defined...
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wavelet based compression schemes belong to the general class of transform coding schemes. We show how the genetic programming approach can be used to optimize such a compression scheme in the sense of rate-distortion...
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ISBN:
(纸本)0819419281
wavelet based compression schemes belong to the general class of transform coding schemes. We show how the genetic programming approach can be used to optimize such a compression scheme in the sense of rate-distortion. The results of optimized wavelet based compression scheme are compared with the JPEG compression standard. A prototype implementation of the method is realized as a distributed, parallel implementation on a heterogeneous Unix network.
We present in the following work, a multiscale edge detection algorithm whose aim is to detect edges of any slope. Our work is based on a generalization of the Canny-Deriche filter, modelized by a more realistic edge ...
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ISBN:
(纸本)0819416274;9780819416278
We present in the following work, a multiscale edge detection algorithm whose aim is to detect edges of any slope. Our work is based on a generalization of the Canny-Deriche filter, modelized by a more realistic edge than the traditional step shape edge. The filter impulse response is used to generate a frame of wavelets. For the merging of the wavelet coefficients, we use a geometrical classifier developed in our laboratory. The segmentation system thus set up and after the training phase does not require any adjustment nor parameter. The main original property of this algorithm is that it leads to a binary edge image without any threshold setting.
In this paper, we propose a new decomposition scheme for spatially adaptive wavelet packets. Contrary to the double tree algorithm, our method is non-uniform and shift-invariant in the time and frequency domains, and ...
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ISBN:
(纸本)0819437646
In this paper, we propose a new decomposition scheme for spatially adaptive wavelet packets. Contrary to the double tree algorithm, our method is non-uniform and shift-invariant in the time and frequency domains, and is minimal for an information cost function. We propose some restrictions to our algorithm to reduce the complexity and permitting us to provide some time-frequency partitions of the signal in agreement with its structure. This new "totally" non-uniform transform, more adapted than Malvar, Packets or dyadic double-tree decomposition, allows the study of all possible time-frequency partitions with the only restriction that the blocks are rectangular. It permits one to obtain a satisfying Time-Frequency representation, and is applied for the study of EEG signals.
This paper proposes a method which utilizes invariant wavelet features for correcting total occlusion in video surveillance applications. The proposed method extracts invariant wavelet features from the pre-occlusion ...
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ISBN:
(纸本)9781424414369
This paper proposes a method which utilizes invariant wavelet features for correcting total occlusion in video surveillance applications. The proposed method extracts invariant wavelet features from the pre-occlusion spatial image of disappearing objects. When new objects are detected during occlusion, their extracted invariant wavelet features are compared to those of lost objects to check for reappearance. When reappearance occurs, the proposed method rebuilds the correct correspondence map between pre-occlusion and post occlusion objects to continue to track the ones that were lost during total occlusion. Our results show that the proposed method is more robust than referenced methods especially when objects change or reverse their motion direction during occlusion.
An image compression method based on wavelet transforms and the human visual system (HVS) is presented in this paper. In the proposed method, we emphasize on the issue of designing a quantizer for wavelet transform co...
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