Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Fundamentals of digital image processing
Fundamentals of digital image processing
Contrast limited adaptive histogram equalization
Graphics gems IV
Digital Image Processing
A Gabor Quotient Image for Face Recognition under Varying Illumination
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Stereo vision based obstacle avoidance path-planning for cross-country intelligent vehicle
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Image segmentation of cervical vertebra in X-ray radiographs using the curve fitting strategy
Proceedings of the 2011 ACM Symposium on Applied Computing
Small retinal vessels extraction towards proliferative diabetic retinopathy screening
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A new non-symmetry and anti-packing model and its application to image contrast enhancement
Computers and Electrical Engineering
A variational approach for exact histogram specification
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Multi-stage visible wavelength and near infrared iris segmentation framework
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A sub-block-based eigenphases algorithm with optimum sub-block size
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Embedded system for contrast enhancement in low-vision
Journal of Systems Architecture: the EUROMICRO Journal
Low-latency histogram equalization for infrared image sequences: a hardware implementation
Journal of Real-Time Image Processing
Exact Histogram Specification for Digital Images Using a Variational Approach
Journal of Mathematical Imaging and Vision
Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients
Digital Signal Processing
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Acquired real-time image sequences, in their original form may not have good viewing quality due to lack of proper lighting or inherent noise. For example, in X-ray imaging, when continuous exposure is used to obtain an image sequence or video, usually low-level exposure is administered until the region of interest is identified. In this case, and many other similar situations, it is desired to improve the image quality in real-time. One particular method of interest, which extensively is used for enhancement of still images, is Contrast Limited Adaptive Histogram Equalization (CLAHE) proposed in [1] and summarized in [2]. This approach is computationally extensive and it is usually used for off-line image enhancement. Because of its performance, hardware implementation of this algorithm for enhancement of real-time image sequences is sought. In this paper, a system level realization of CLAHE is proposed, which is suitable for VLSI or FPGA implementation. The goal for this realization is to minimize the latency without sacrificing precision.