A simple and effective histogram equalization approach to image enhancement

Cheng, Heng-Da; Shi, Xiangjun

doi:10.1016/j.dsp.2003.07.002

Cited by 312 publications

(128 citation statements)

References 23 publications

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“…One of the most well known techniques [9] for image enhancement was based on the grey scale of the data. The data depends on the frequency distribution of the pixels.…”

Section: Histogram Equalizationmentioning

confidence: 99%

Hardware Acceleration of Histogram Equalization and Image Sharpening Filter on NIOSII Processor Based SOC on FPGA

Kishore¹,

Addanki²

2011

IJCA

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In this paper, we presents a framework for hardware accelerating methods for video post processing system implemented on FPGA. The histogram equalization and image-sharpening filter are the algorithms ported onto the SOC having Altera NIOS-II soft processor. Custom instructions are chosen by identifying the most frequently used tasks in the algorithm and the instruction set of NIOS-II processor has been extended. Saturation and the Histogram are the new instructions added to the processor that are implemented in hardware and interfaced to the NIOS-II processor. The software implementation of the algorithms has been modified to use the new instructions added for computing the saturation and histogram calculation. Performance of the software implementation of the histogram equalization and sharpening algorithms is boosted by these new instructions added to the NIOS-II processor. The comparison shows that the implemented tasks have been accelerated by -multiple‖ times. The saturation instruction is generic instruction, which can be used in many Image processing applications. The benefit of speed is obtained at the cost of very small hardware resources.

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“…One of the most well known techniques [9] for image enhancement was based on the grey scale of the data. The data depends on the frequency distribution of the pixels.…”

Section: Histogram Equalizationmentioning

confidence: 99%

Hardware Acceleration of Histogram Equalization and Image Sharpening Filter on NIOSII Processor Based SOC on FPGA

Kishore¹,

Addanki²

2011

IJCA

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“…Peaks in the image histogram (indicating commonly used grey levels) are widened, while the valleys are compressed [21]. …”

Section: C) Histogram Equalizationmentioning

confidence: 99%

Measurement and Analysis of the Diameter of Appendix Based on Ultrasound Images

Lam¹,

Pahl²,

Abduljabbar³

et al. 2014

IJBBB

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Abstract-One of the most common cause of emergency surgery of the abdomen is acute appendicitis. Early and accurate diagnosis of appendicitis can decrease the morbidity and hospital cost by reducing the delay in diagnosis of appendicitis and its associated complications. In current clinical practice, the measurement of the outer appendiceal diameter by sonographers has been used as one of the indication to confirm acute appendicitis, where the value greater than 6 mm is considered to be a sign of acute appendicitis. However, since ultrasound image itself is in low quality due to speckle noise, error in manual measurement by the sonographers might occur due to wrong detection of the appendiceal edge or wrong placement of the calliper. Thus, we propose certain image processing techniques to enhance the image quality to help sonographers in performing a better diagnosis. This paper proposed a series of image processing method including image enhancement, image segmentation and edge detection before measuring the appendiceal. Selection of image enhancement method is made based on MSE and PSNR values while selection of image segmentation method is made based on the segmented image and execution time. Ten trials of measurement by sonographers using ultrasound and measurement after image processing were gathered. Statistical analyses of both measurements were computed. Mean and standard deviation for the sonographers measurements and measurements after image processing are 4.937±0.14mm and 4.613710±0.08mm respectively. Sonographers measurement showed higher variability compared to measurement after image processing thus measuring the appendiceal diameter after image processing can be helpful for a better diagnosis.

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“…In their method, the assumption was that the attenuation increased as the backscatter increased. Although image processing techniques such as histogram equalisation (see, for example, Cheng and Shi 2004) can be used as an alternative for attenuation compensation to improve perceived image visualisation, quantification of image intensity based on this kind of approach is generally not plausibly justified.…”

Section: Introductionmentioning

confidence: 99%

Attenuation Correction in Ultrasound Contrast Agent Imaging: Elementary Theory and Preliminary Experimental Evaluation

Tang

Mari

Wells

et al. 2008

Ultrasound in Medicine & Biology

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-Progress in imaging and quantification of tissue perfusion using ultrasound (US) and microbubble contrast agents has been undermined by the lack of an effective automatic attenuation correction technique. In this paper, an elementary model of the US attenuation processes for microbubble contrast enhanced imaging is developed. In the model, factors such as nonlinear bubble scattering, nonlinear attenuation, attenuation to both fundamental and harmonic, and US beam profile are considered. Methods are proposed for fast formation of images with automatic attenuation correction based on the model. In the proposed method, linear tissue echoes are extracted and filtered, and then used to compensate for the attenuation in nonlinear bubble echoes at the same location to produce quantities that are a truer representation of bubble concentration. The technique does not require additional measurements and can be implemented in real time. Preliminary experiments on laboratory phantoms consisting of bubbles and tissue-mimicking materials are presented and the effectiveness of the proposed method is supported by improvements in image quality compared with unprocessed data. This development is an important step towards real-time quantitative contrast US imaging.

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A simple and effective histogram equalization approach to image enhancement

Cited by 312 publications

References 23 publications

Hardware Acceleration of Histogram Equalization and Image Sharpening Filter on NIOSII Processor Based SOC on FPGA

Hardware Acceleration of Histogram Equalization and Image Sharpening Filter on NIOSII Processor Based SOC on FPGA

Measurement and Analysis of the Diameter of Appendix Based on Ultrasound Images

Attenuation Correction in Ultrasound Contrast Agent Imaging: Elementary Theory and Preliminary Experimental Evaluation

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