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Efficient, high-quality image contour detection

by Bryan Catanzaro, Bor-yiing Su, Narayanan Sundaram, Yunsup Lee, Mark Murphy, Kurt Keutzer - In IEEE International Conference on Computer Vision , 2009
"... Image contour detection is fundamental to many image analysis applications, including image segmentation, object recognition and classification. However, highly accurate image contour detection algorithms are also very computationally intensive, which limits their applicability, even for offline bat ..."
Abstract - Cited by 32 (1 self) - Add to MetaCart
implementation on highly parallel, commodity processors from Nvidia, our contour detector provides uncompromised contour accuracy, with an F-metric of 0.70 on the Berkeley Segmentation Dataset. Runtime is reduced from 4 minutes to 1.8 seconds. The efficiency gains we realize enable high-quality image contour

Fast and High-Quality Image Blending on Mobile Phones

by Yingen Xiong , Kari Pulli
"... Abstract-We present a fast and high-quality image stitching approach for creating high-resolution and high-quality panoramic images on mobile devices. In the approach, a sequential panorama stitching procedure is created with color and luminance compensation for reducing differences between source ..."
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Abstract-We present a fast and high-quality image stitching approach for creating high-resolution and high-quality panoramic images on mobile devices. In the approach, a sequential panorama stitching procedure is created with color and luminance compensation for reducing differences between source

Implementation Details for “Predictable High-Quality Image Completion”

by Image Completion Pseudocode
"... In this supplementary document we provide commented pseudocode for our image completion algorithm. It is more or less a straight-forward implementation of [Wexler et al. 2007] using PatchMatch [Barnes et al. 2009] for fast approximate nearestneighbor search. Refer to Figure 1 for a list and explanat ..."
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In this supplementary document we provide commented pseudocode for our image completion algorithm. It is more or less a straight-forward implementation of [Wexler et al. 2007] using PatchMatch [Barnes et al. 2009] for fast approximate nearestneighbor search. Refer to Figure 1 for a list

High-quality image-based . . . Of Real-world Environments

by Matthew Uyttendaele, Antonio Criminisi, Sing Bing Kang, Simon Winder, Richard Hartley, Richard Szeliski , 2003
"... ..."
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Super Resolution methods to achieve high quality imaging

by Prof. Bhushan V. Patil, Mayuri D. Patil, Namrata R. Shaha, Dipali A. Shaha
"... Now a day the increase in the quality of images is becoming need of the multimedia applications. The quality of the image can be improved by increasing the resolution. There is a limitation for the spatial resolution of an image captured by any present image acquisition device. The increase in the o ..."
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of an image. We present an overview of existing SR methods and address the motion estimation and optical blur methods of super resolution to achieve high quality imaging with different optical zoom of low resolution camera. The quality of images is significantly improved and high resolution imaging

High Quality Image Synthesis on Distributed Memory Multiprocessors

by Thierry Priol
"... : The production of realistic images generated by computer requires a huge amount of computation. The use of highly parallel computers allows this process to be performed faster. Distributed memory parallel computers (DMPCs) offer an attractive performance/cost ratio. However, several crucial proble ..."
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which is able to render high quality images. The main interest of this method lies in the fa...

Fuzzy rendering for high quality image generation

by Andrew James, Harman Willmott , 1993
"... This thesis is concerned with the field of high-quality image rendering. It describes research into a system for rendering a scene so that the picture produced is accurate to some specified limit. We refer to the system as “Fuzzy Rendering, ” because it deals with ranges of metrics, rather than prec ..."
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This thesis is concerned with the field of high-quality image rendering. It describes research into a system for rendering a scene so that the picture produced is accurate to some specified limit. We refer to the system as “Fuzzy Rendering, ” because it deals with ranges of metrics, rather than

Comparison of Polarimetric Retinal Nerve Fiber Analyzer Parameters for a Single High Quality Image and the Mean Image from Three High Quality Images

by Jen-chia Tsai Md
"... Background: To find the correlations and differences between the nerve fiber layer para-meters of a GDx (polarimetric retinal nerve fiber analyzer) in single high quality images and those in the mean image from three high quality images. Methods: The results of scanning laser polarimetry were select ..."
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Background: To find the correlations and differences between the nerve fiber layer para-meters of a GDx (polarimetric retinal nerve fiber analyzer) in single high quality images and those in the mean image from three high quality images. Methods: The results of scanning laser polarimetry were

Astola: “DCT Based High Quality Image Compression

by Nikolay Ponomarenko, Vladimir Lukin, Karen Egiazarian, Jaakko Astola - Proceedings of 14th Scandinavian Conference on Image Analysis , 2005
"... Abstract. DCT based image compression using blocks of size 32x32 is considered. An effective method of bit-plane coding of quantized DCT coefficients is proposed. Parameters of post-filtering for removing of blocking artifacts in decoded images are given. The efficiency of the proposed method for te ..."
Abstract - Cited by 8 (6 self) - Add to MetaCart
for test images compression is analyzed. It is shown that the proposed method is able to provide the quality of decoding images higher than for JPEG2000 by up to 1.9 dB. 1

Optimized Error Diffusion for High Quality Image Display

by B. W. Kolpatzik, C.A. Bouman - Journal of Electronic Imaging , 1992
"... Displaying natural images on an 8 bit computer monitor requires a substantial reduction of physically distinct colors. Simple minimum mean squared error (MMSE) quantization with 8 levels of red and green and 4 levels of blue yields poor image quality. A powerful means to improve the subjective quali ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
Displaying natural images on an 8 bit computer monitor requires a substantial reduction of physically distinct colors. Simple minimum mean squared error (MMSE) quantization with 8 levels of red and green and 4 levels of blue yields poor image quality. A powerful means to improve the subjective
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