1,969 research outputs found
Design of Novel Algorithm and Architecture for Gaussian Based Color Image Enhancement System for Real Time Applications
This paper presents the development of a new algorithm for Gaussian based
color image enhancement system. The algorithm has been designed into
architecture suitable for FPGA/ASIC implementation. The color image enhancement
is achieved by first convolving an original image with a Gaussian kernel since
Gaussian distribution is a point spread function which smoothen the image.
Further, logarithm-domain processing and gain/offset corrections are employed
in order to enhance and translate pixels into the display range of 0 to 255.
The proposed algorithm not only provides better dynamic range compression and
color rendition effect but also achieves color constancy in an image. The
design exploits high degrees of pipelining and parallel processing to achieve
real time performance. The design has been realized by RTL compliant Verilog
coding and fits into a single FPGA with a gate count utilization of 321,804.
The proposed method is implemented using Xilinx Virtex-II Pro XC2VP40-7FF1148
FPGA device and is capable of processing high resolution color motion pictures
of sizes of up to 1600x1200 pixels at the real time video rate of 116 frames
per second. This shows that the proposed design would work for not only still
images but also for high resolution video sequences.Comment: 15 pages, 15 figure
Image enhancement using fuzzy intensity measure and adaptive clipping histogram equalization
Image enhancement aims at processing an input
image so that the visual content of the output image is more
pleasing or more useful for certain applications. Although
histogram equalization is widely used in image enhancement due
to its simplicity and effectiveness, it changes the mean brightness
of the enhanced image and introduces a high level of noise and
distortion. To address these problems, this paper proposes
image enhancement using fuzzy intensity measure and adaptive
clipping histogram equalization (FIMHE). FIMHE uses fuzzy
intensity measure to first segment the histogram of the original
image, and then clip the histogram adaptively in order to
prevent excessive image enhancement. Experiments on the
Berkeley database and CVF-UGR-Image database show that
FIMHE outperforms state-of-the-art histogram equalization
based methods
Color Histogram Equalization using Probability Smoothing
Publication in the conference proceedings of EUSIPCO, Florence, Italy, 200
Review on Efficient Contrast Enhancement Technique for Low Illumination Color Images
A digital color image, as its fundamental purpose requires, is to provide a perception of the scene to a human viewer or a computer for carrying out automation tasks such as object recognition. An image of high quality that could truly represent the captured object and the scene is hence in great demand.Contrast is an important factor in any subjective evaluation of image quality. It is the difference in visual properties that makes an object distinguishable from other object and background. On the contrary, the human visual perception is interested in hue (H), saturation (S) and intensity (I) attributes that are carried by the color image. Therefore, when the image has to be processed, most approaches convert the RGB space into some convenient working signal spaces that are close to human perceptions
Implementation of Adaptive Unsharp Masking as a pre-filtering method for watermark detection and extraction
Digital watermarking has been one of the focal points of research interests in order to provide multimedia security in the last decade. Watermark data, belonging to the user, are embedded on an original work such as text, audio, image, and video and thus, product ownership can be proved. Various robust watermarking algorithms have been developed in order to extract/detect the watermark against such attacks. Although watermarking algorithms in the transform domain differ from others by different combinations of transform techniques, it is difficult to decide on an algorithm for a specific application. Therefore, instead of developing a new watermarking algorithm with different combinations of transform techniques, we propose a novel and effective watermark extraction and detection method by pre-filtering, namely Adaptive Unsharp Masking (AUM). In spite of the fact that Unsharp Masking (UM) based pre-filtering is used for watermark extraction/detection in the literature by causing the details of the watermarked image become more manifest, effectiveness of UM may decrease in some cases of attacks. In this study, AUM has been proposed for pre-filtering as a solution to the disadvantages of UM. Experimental results show that AUM performs better up to 11\% in objective quality metrics than that of the results when pre-filtering is not used. Moreover; AUM proposed for pre-filtering in the transform domain image watermarking is as effective as that of used in image enhancement and can be applied in an algorithm-independent way for pre-filtering in transform domain image watermarking
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