In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information ...In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.展开更多
Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. T...Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima(WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean(μ),standard deviation(?), mean square error(MSE) and PSNR(peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement.展开更多
To improve the quality of ultrasonic elastography, by taking the advantage of code excitation and frequency compounding, a transmitting-side multi-frequency with coded excitation for elastography （TFCCE） was propose...To improve the quality of ultrasonic elastography, by taking the advantage of code excitation and frequency compounding, a transmitting-side multi-frequency with coded excitation for elastography （TFCCE） was proposed. TFCCE adopts the chirp signal excitation scheme and strikes a balance in the selection of sub-signal bandwidth, the bandwidth overlap and the number of sub-strain image based on theoretical derivation, so as to further improve the quality of elastic image. Experiments have proved that, compared with the other optimizing methods, the elastographyic signal-to-noise ratio（Re-SN） and contrast-to-noise ratio（Re-CN） are improved significantly with different echo signal-to-noise ratios （ReSN） and attenuation coefficients. When ReSN is 50 dB, compared with short pulse, Rc-SN and Re-CN obtained by TFCCE increase by 53% and 143%, respectively. Moreover, in a deeper investigation （85-95 mm）, the image has lower strain noise and clear details. When the attenuation coefficient is in the range of 0-1 dB/（cm.MHz）, Re-SN and Re-CN obtained by TFCCE can be kept in moderate ranges of 5〈Re-SN〈6.8 and 11.4〈Re-CN〈15.2, respectively. In particular, for higher tissue attenuation, the basic image quality cannot be ensured with short pulse excitation, while mediocre quality strain figure can be obtained by TFCCE. Therefore, the TFCCE technology can effectively improve the elastography quality and can be applied to ultrasonic clinical trials.展开更多
基金Project(61071162) supported by the National Natural Science Foundation of China
文摘In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.
基金Projects(61376076,61274026,61377024)supported by the National Natural Science Foundation of ChinaProjects(12C0108,13C321)supported by the Scientific Research Fund of Hunan Provincial Education Department,ChinaProjects(2013FJ2011,2014FJ2017,2013FJ4232)supported by the Science and Technology Plan Foundation of Hunan Province,China
文摘Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima(WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean(μ),standard deviation(?), mean square error(MSE) and PSNR(peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement.
基金Project(2013GZX0147-3) supported by the Natural Science Foundation of Sichuan Province,China
文摘To improve the quality of ultrasonic elastography, by taking the advantage of code excitation and frequency compounding, a transmitting-side multi-frequency with coded excitation for elastography （TFCCE） was proposed. TFCCE adopts the chirp signal excitation scheme and strikes a balance in the selection of sub-signal bandwidth, the bandwidth overlap and the number of sub-strain image based on theoretical derivation, so as to further improve the quality of elastic image. Experiments have proved that, compared with the other optimizing methods, the elastographyic signal-to-noise ratio（Re-SN） and contrast-to-noise ratio（Re-CN） are improved significantly with different echo signal-to-noise ratios （ReSN） and attenuation coefficients. When ReSN is 50 dB, compared with short pulse, Rc-SN and Re-CN obtained by TFCCE increase by 53% and 143%, respectively. Moreover, in a deeper investigation （85-95 mm）, the image has lower strain noise and clear details. When the attenuation coefficient is in the range of 0-1 dB/（cm.MHz）, Re-SN and Re-CN obtained by TFCCE can be kept in moderate ranges of 5〈Re-SN〈6.8 and 11.4〈Re-CN〈15.2, respectively. In particular, for higher tissue attenuation, the basic image quality cannot be ensured with short pulse excitation, while mediocre quality strain figure can be obtained by TFCCE. Therefore, the TFCCE technology can effectively improve the elastography quality and can be applied to ultrasonic clinical trials.
