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Méthodes et algorithmes de dématriçage et de filtrage du bruit pour la photographie numérique

Abstract : Digital cameras are now present everywhere. They are commonly included in portable digital devices such as mobile phones and personal digital assistants. In spite of constant improvements in terms of computing power and complexity, the digital imaging chain quality, including sensor and lenses system, is still limited by space and cost constraints. An important number of degradations are introduced by this chain that significantly decrease overall image quality : including blurring effects, geometric distortions, color artefacts, moiré effects, static and dynamic noise. Correcting these defects in an algorithmic way, using the increasing power of embedded processing architecture present in mobile phones and PDAs may appear like an interesting solution. In this thesis we are especially interested in reducing two major defects of the sensor acquisition chain : Bayer matrix demosaicing artefacts and photon noise. In the first part, we describe the general imaging chain commonly used in digital cameras and video devices. We show the function, the inner working and the defects introduced by each of its elements. Finally we exhibit possible ways to correct these defects using algorithmic solutions. In the second part, we introduce the principle of Bayer demosaicing. We present the state of the art and we propose a new method based on a directed interpolation principle. Our method yields a good image quality while retaining a low computational complexity. We then enumerate several noise sources present in imaging digital sensors and their dependencies with imaging conditions. We are particularly interested in local algorithms and more specifically in the bilateral filter. After presenting the state of the art in denoising algorithm, we propose a new adaptive bilateral filter for sensor colour mosaic denoising. In the third part, we present the implementation, the optimization and the execution simulation of the proposed demosaicing and denoising algorithms. The implementation target is the TM3270 TriMedia processor from NXP Semiconductors. We show that it is possible to process 5 megapixels images in less than 0.5 seconds and more than 25 images per second at VGA resolution. Finally, for standardization, execution speed and power consumption reasons, we describe a dedicated architecture for our proposed demosaicing algorithm. This architecture improves the execution speed by a factor of 10 compared to the TriMedia TM3270 processor
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Submitted on : Friday, July 9, 2010 - 8:36:25 AM
Last modification on : Wednesday, February 26, 2020 - 7:06:06 PM
Long-term archiving on: : Monday, October 11, 2010 - 9:43:05 AM


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  • HAL Id : tel-00499252, version 1


Harold Phelippeau. Méthodes et algorithmes de dématriçage et de filtrage du bruit pour la photographie numérique. Autre [cs.OH]. Université Paris-Est, 2009. Français. ⟨NNT : 2009PEST1002⟩. ⟨tel-00499252⟩



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