Spectral computed tomography(CT) based on photon counting detectors(PCDs) is a well-researched topic in the field of X-ray imaging. When PCD is applied in a spectral CT system, the PCD energy thresholds must be carefu...Spectral computed tomography(CT) based on photon counting detectors(PCDs) is a well-researched topic in the field of X-ray imaging. When PCD is applied in a spectral CT system, the PCD energy thresholds must be carefully selected, especially for K-edge imaging, which is an important spectral CT application. This paper presents a threshold selection method that yields better-quality images in K-edge imaging. The main idea is to optimize the energy thresholds ray-by-ray according to the targeted component coefficients, followed by obtaining an overall optimal energy threshold by frequency voting. A low-dose pre-scan is used in practical implementations to estimate the line integrals of the component coefficients for the basis functions. The variance of the decomposed component coefficients is then minimized using the Cramer–Rao lower bound method with respect to the energy thresholds. The optimal energy thresholds are then used to take a full scan and gain better image reconstruction with less noise than would be given by a full scan using the non-optimal energy thresholds. Simulations and practical experiments on imaging iodine and gadolinium solutions, which are commonly used as contrast agents in medical applications, were used to validate the method. The noise was significantly reduced with the same dose relative to the non-optimal energy thresholds in both simulations and in practical experiments.展开更多
Human eye can generally distinguish objects from each other or from their background, if the difference in luminance or color is large. This paper concentrates on the luminance portion and makes an attempt to characte...Human eye can generally distinguish objects from each other or from their background, if the difference in luminance or color is large. This paper concentrates on the luminance portion and makes an attempt to characterize perception detection to varying contrast which is explained in contrast sensitivity terms. This is accomplished using sinusoidal test patterns. Influence of illumination on perception threshold is also shown in this paper. Practical measurements are done using a calibrated monitor with image capture accomplished with a 1/4' 1.3M camera module system.展开更多
To refine the assumption that the contrast threshold of the human eye(Crt)remains constant in general visibility theory,we integrated an artificial intelligence-based approach with a mechanistic model(AI-SD)to derive ...To refine the assumption that the contrast threshold of the human eye(Crt)remains constant in general visibility theory,we integrated an artificial intelligence-based approach with a mechanistic model(AI-SD)to derive the equivalent contrast threshold at 488 nm(C_(488))from remote sensing reflectance on a pixel-by-pixel basis.The derived C_(488) was then applied to estimate Secchi depth(Z_(sd)).We trained and validated the AI-SD model using an extensive fieldmeasured dataset(N=1577)encompassing oceanic,coastal,and inland waters and compared its performance with a traditional mechanistic model.Our findings indicate that C_(488) theoretically ranges from 1.85×10^(−5) sr^(−1) to 0.138 sr^(−1) and improves the accuracy of Z_(sd) estimates from field-measured or satellite-derived remote sensing reflectance(R_(rs))by over 10%compared to the traditional model.Furthermore,applying the AI-SD model to global R_(rs) data revealed that C_(488) exhibits spatial and temporal variability across the world’s oceans.We linked this variability to the observed,yet traditionally unexplained,non-monotonic relationship between Z_(sd) and solar zenith angle-related water-leaving radiance.These results highlight the potential for enhancing global water transparency monitoring via ocean color satellites by incorporating accurate,pixel-level C_(488) values.展开更多
基金supported by Grants from National key research and development program(No.2016YFF0101304)the National Natural Science Foundation of China(Nos.61771279,11435007)
文摘Spectral computed tomography(CT) based on photon counting detectors(PCDs) is a well-researched topic in the field of X-ray imaging. When PCD is applied in a spectral CT system, the PCD energy thresholds must be carefully selected, especially for K-edge imaging, which is an important spectral CT application. This paper presents a threshold selection method that yields better-quality images in K-edge imaging. The main idea is to optimize the energy thresholds ray-by-ray according to the targeted component coefficients, followed by obtaining an overall optimal energy threshold by frequency voting. A low-dose pre-scan is used in practical implementations to estimate the line integrals of the component coefficients for the basis functions. The variance of the decomposed component coefficients is then minimized using the Cramer–Rao lower bound method with respect to the energy thresholds. The optimal energy thresholds are then used to take a full scan and gain better image reconstruction with less noise than would be given by a full scan using the non-optimal energy thresholds. Simulations and practical experiments on imaging iodine and gadolinium solutions, which are commonly used as contrast agents in medical applications, were used to validate the method. The noise was significantly reduced with the same dose relative to the non-optimal energy thresholds in both simulations and in practical experiments.
文摘Human eye can generally distinguish objects from each other or from their background, if the difference in luminance or color is large. This paper concentrates on the luminance portion and makes an attempt to characterize perception detection to varying contrast which is explained in contrast sensitivity terms. This is accomplished using sinusoidal test patterns. Influence of illumination on perception threshold is also shown in this paper. Practical measurements are done using a calibrated monitor with image capture accomplished with a 1/4' 1.3M camera module system.
基金The National Key R&D Program of China under contract No.2022YFB3903003-2the Shaanxi Key Research and Development Program under contract No.2022ZDLSF06-09.
文摘To refine the assumption that the contrast threshold of the human eye(Crt)remains constant in general visibility theory,we integrated an artificial intelligence-based approach with a mechanistic model(AI-SD)to derive the equivalent contrast threshold at 488 nm(C_(488))from remote sensing reflectance on a pixel-by-pixel basis.The derived C_(488) was then applied to estimate Secchi depth(Z_(sd)).We trained and validated the AI-SD model using an extensive fieldmeasured dataset(N=1577)encompassing oceanic,coastal,and inland waters and compared its performance with a traditional mechanistic model.Our findings indicate that C_(488) theoretically ranges from 1.85×10^(−5) sr^(−1) to 0.138 sr^(−1) and improves the accuracy of Z_(sd) estimates from field-measured or satellite-derived remote sensing reflectance(R_(rs))by over 10%compared to the traditional model.Furthermore,applying the AI-SD model to global R_(rs) data revealed that C_(488) exhibits spatial and temporal variability across the world’s oceans.We linked this variability to the observed,yet traditionally unexplained,non-monotonic relationship between Z_(sd) and solar zenith angle-related water-leaving radiance.These results highlight the potential for enhancing global water transparency monitoring via ocean color satellites by incorporating accurate,pixel-level C_(488) values.
