Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform

Bai, Xiangzhi; Zhou, Fugen; Xue, Bin

doi:10.1016/j.infrared.2010.12.001

Cited by 98 publications

(45 citation statements)

References 25 publications

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“…Based on the above analysis, a multiscale new Top-Hat transform (MSNTH) based algorithm [8] was proposed for Infrared image enhancement. Instead of using single structuring element, the multi-scale new top-hat transform algorithm used two different multi-scale structuring elements with increasing sizes for extracting regions of interest with different sizes at different scales.…”

Section: Direct Contrast Enhancement Techniquesmentioning

confidence: 99%

“…Multiscale feature extraction was carried out by sequential toggle operator resulting in smoothed bright and dim image features. The pixel wise comparing strategy [6], [8], [49] has been considered an effective way of feature extraction representing the fine details of image. The pixel wise extracted bright features are combined together for all scales forming multiscale image feature extraction.…”

Section: Direct Contrast Enhancement Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent Based Image Enhancement using Direct and In-Direct Contrast Enhancement Techniques – A Comparative Survey

Supriya¹,

Subaji²

2017

IJSIP

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Section: Direct Contrast Enhancement Techniquesmentioning

confidence: 99%

Section: Direct Contrast Enhancement Techniquesmentioning

confidence: 99%

Intelligent Based Image Enhancement using Direct and In-Direct Contrast Enhancement Techniques – A Comparative Survey

Supriya¹,

Subaji²

2017

IJSIP

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“…With the fact that, the facial image recognition will always, give a matching output or closest possible output image for every input image irrespective of the authenticity, the universal smart GUI tool is proposed and designed to perform image forgery detection with the high accuracy of Â±2% error rate. Bai et al (2011) have proposed an infrared image enhancement algorithm through contrast enhancement. In this proposed method based on multiscale new top-hat transform.…”

Section: Related Researches: a Reviewmentioning

confidence: 99%

Enhancing Digital Images Through Cuckoo Search Algorithm in Combination with Morphological Operation

Babu¹,

Sunitha²

2015

Journal of Computer Science

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Abstract:This study presents an image enhancement approach to Cuckoo Search Algorithmin with Morphological Operation. At the present time, in many image processing applications digital images are developed. Machine vision, computer interfaces, manufacturing, compression for storage and more are some of the fields of image processing application. Before using it in any applications the image has to be managed, such processing is said to be image enhancement. We propose a method to combine with an enhancing digital images through cuckoo search algorithmin and morphological operation. Therefore, the appearance of noise produces distortion in an image and thus the image will be unattractive. This decreases the discernibility of many features inside the images. In this study, we are working to overcome this drawback by getting an improved contrast value after converting the color image into grayscale image. The fundamental characteristic of this CS algorithm is that the amplitudes of its components can objectively reflect the contribution of the gray levels to the representation of image information for the best contrast value of an image. After selecting the best contrast value of an image in CS algorithm, morphological operations have to be done. In morphological operations, the intensity parameters of the image are adjusted to improve its quality. Experimental results demonstrate that the proposed approach is converted into original color image without noise and adaptive process to enhance the quality of images.

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“…For the same purpose, hit-or-miss transform based morphological approach is proposed in [15]. Multiscale tophat transform is used in contrast enhancement in [16] and the performance is compared with histogram and morphological based approaches using fuzziness index for sea and sky backgrounds. IR-IE based on human visual system is proposed in [17] using multifractal theory.…”

Section: Related Workmentioning

confidence: 99%

Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems

Karali

Okman

Aytaç

2011

Infrared Physics & Technology

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Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform

Cited by 98 publications

References 25 publications

Intelligent Based Image Enhancement using Direct and In-Direct Contrast Enhancement Techniques – A Comparative Survey

Intelligent Based Image Enhancement using Direct and In-Direct Contrast Enhancement Techniques – A Comparative Survey

Enhancing Digital Images Through Cuckoo Search Algorithm in Combination with Morphological Operation

Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems

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