Amani Chaker

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In this paper, we are interested in studying the impact of the compression on the performances of some wavelet-based retrieval systems. Firstly, we show that the quantization operation of JPEG2000 has a negative effect on the performance of these contentbased image retrieval systems for a given feature extraction method. Moreover, in this work, we aim at(More)
This paper deals with the problem of image retrieval when the database is presented in a compressed form, by using typically the JPEG2000 encoding scheme based on wavelet transform followed by an uniform scalar quantization. The state-of-the-art method aims at applying a preprocessing step before the feature extraction to reduce the difference in the(More)
Recent research efforts have been devoted to the improvement of image retrieval systems when datasets are represented in a compressed form. In this context, new studies have shown that compression has a negative impact on the performances of the traditional retrieval systems. In this work, we are mainly interested in designing an efficient retrieval(More)
The great interest of stereo images in several applications has led to the proliferation of huge and ever growing image databases. Therefore, there is an urgent demand for an effective Content Based Image Retrieval (CBIR) system devoted to stereo images. To meet such a demand, this paper proposes new wavelet-based retrieval approaches that exploit not only(More)
With the great demand for storing and transmitting images as well as their managing, the retrieval of compressed images is a field of intensive research. While most of the works have been devoted to the case of losslessly encoded images (by extracting features from the unquantized transform coefficients), new studies have shown that lossy compression has a(More)
Ongoing developments in stereoscopic display technologies have led to the proliferation of huge stereo image databases. Therefore, the design of an appropriate Content Based Image Retrieval (CBIR) system for stereo images is an important emerging issue. In this paper, we propose a novel retrieval method which exploits simultaneously the spatial and(More)
Recent research works have shown the impact of the quantization techniques on the performance of standard image retrieval systems when datasets are compressed in a lossy mode. In this work, we propose to design an efficient retrieval method well adapted to wavelet-based compressed images. Our objective is to recover features of the original image (herein(More)
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