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Image Processing Workshop (WNYIPW), 2011 IEEE Western New York

Date 14-14 Nov. 2011

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Displaying Results 1 - 7 of 7
  • [Front and back cover]

    Publication Year: 2011 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | PDF file iconPDF (253 KB)  
    Freely Available from IEEE
  • Unsupervised learning of video content using Self-Organizing Maps

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (657 KB) |  | HTML iconHTML  

    Video classification and retrieval is currently performed manually by individuals adding semantic annotation or creating a description of the videos. Current algorithmic methods often suffer from semantic gap between visual content and human interpretation. This paper proposes a biologically inspired system that automatically cluster videos based on visual attributes. For feature extraction, each ... View full abstract»

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  • Interactive display using depth and RGB sensors for face and gesture control

    Publication Year: 2011 , Page(s): 1 - 4
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1243 KB) |  | HTML iconHTML  

    This paper introduces an interactive display system guided by a human observer's gesture, facial pose, and facial expression. The Kinect depth sensor is used to detect and track an observer's skeletal joints while the RGB camera is used for detailed facial analysis. The display consists of active regions that the observer can manipulate with body gestures and secluded regions that are activated th... View full abstract»

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  • Engineered phase window for extended depth of focus

    Publication Year: 2011 , Page(s): 1 - 3
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1231 KB) |  | HTML iconHTML  

    Wavefront coding is successful at decreasing the focus dependence of an optical system. These systems require image processing and additional optical surfaces. We develop a phase surface placed near the image plane to engineer the point spread function into a similar shape. The resulting system contains a beam shaping optic that utilizes the already-present detector window and provides more flexib... View full abstract»

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  • Attitude determination using a photon counting star tracker

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1133 KB) |  | HTML iconHTML  

    This paper describes a path toward the development of theory for using a photon counting camera as a star tracker for spacecraft attitude estimation. The benefit of using a photon counting camera is that star data can be sampled at a faster rate while allowing one to measure very dim stars, increasing the number of stars available for attitude estimation. The development of a noise model is discus... View full abstract»

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  • Block-sorting transformations with pseudo-distance technique for lossless compression of color-mapped images

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1164 KB) |  | HTML iconHTML  

    Color-mapped images are widely used in many applications, especially in WWW, and are usually compressed with Graphic Interchange Format (GIF) without any loss. In our recent work, we showed that further compression gains can be achieved for color-mapped images over GIF when a structured arithmetic coder is used along with the pseudo-distance metric, instead of a Huffman coder as suggested by other... View full abstract»

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  • Adaptive Order-Statistic Filters for optimal non-Gaussian noise suppression

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2782 KB) |  | HTML iconHTML  

    This paper presents an adaptive Order-Statistic Filter (OSF) that maximizes the gain in image SNR. In particular, this distribution-independent non-linear filter approximates the optimal filter when the noise is not Gaussian (e.g., speckle-type clutter, Gamma noise, etc.). Simulation results quantitatively demonstrate the superior performance of the adaptive OSF over popular linear and non-linear ... View full abstract»

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