Images acquired under deprived weather environment are frequently corrupted due to the presence of haze, mist, fog or other aerosols in a form of noise. Haze elimination is essential in computer vision and computation...Images acquired under deprived weather environment are frequently corrupted due to the presence of haze, mist, fog or other aerosols in a form of noise. Haze elimination is essential in computer vision and computational photography applications. Generally, there is the existence of numerous approaches towards haze removal which are mostly meant for hazy images under daytime environments. Although the potency of these proposed approaches has been comprehensively established on daylight hazy images. However these procedures inherit significant limitations on images influenced by night-time hazy environments. Since night time haze removal dehazing remains an ill-posed problem, we proposed a novel method for night-time single image dehazing which is efficient under night-time environments. The proposed scheme is a dark channel-based local image dehazing procedure that locally estimates the atmospheric intensity for each selected mask on a corrupted image independently and not the entire image. This is done in order to overcome the challenge of night-scenes that are exposed to multiple/artificial lights source and spatially non-uniform environmental illumination. We performed an adaptive filtering on the combined dehazed masks to improve the degraded image. We validated the supremacy of the proposed approach in terms of speed and robustness through computer-based experiments. Conclusively, we displayed comparison results with state-of-the-art and extensively emphasized the comparative advantage of our scheme.展开更多
The haze defects on p-type (111) silicon wafers were investigated by means of chemical etching, Fouriertransform infra-red microscopy (FTIR), spreading resistance measurement. secondary ion mass spectroscopy(SLMS), tr...The haze defects on p-type (111) silicon wafers were investigated by means of chemical etching, Fouriertransform infra-red microscopy (FTIR), spreading resistance measurement. secondary ion mass spectroscopy(SLMS), transmission electron microscopy (TEM) equipped with an energy-dispersive X-ray spectrometer(EDX). The haze defects are the precipitates of silicide of metal impurities (Fe, Ni) on the wafer surface.The formation of haze defects can efficiently be inhibited by utilizing the technology of fast neutronirradiation combined with the internal gettering (IG), and then, the formation and removement mechanismof the haze defects have been discussed in this paper.展开更多
文摘Images acquired under deprived weather environment are frequently corrupted due to the presence of haze, mist, fog or other aerosols in a form of noise. Haze elimination is essential in computer vision and computational photography applications. Generally, there is the existence of numerous approaches towards haze removal which are mostly meant for hazy images under daytime environments. Although the potency of these proposed approaches has been comprehensively established on daylight hazy images. However these procedures inherit significant limitations on images influenced by night-time hazy environments. Since night time haze removal dehazing remains an ill-posed problem, we proposed a novel method for night-time single image dehazing which is efficient under night-time environments. The proposed scheme is a dark channel-based local image dehazing procedure that locally estimates the atmospheric intensity for each selected mask on a corrupted image independently and not the entire image. This is done in order to overcome the challenge of night-scenes that are exposed to multiple/artificial lights source and spatially non-uniform environmental illumination. We performed an adaptive filtering on the combined dehazed masks to improve the degraded image. We validated the supremacy of the proposed approach in terms of speed and robustness through computer-based experiments. Conclusively, we displayed comparison results with state-of-the-art and extensively emphasized the comparative advantage of our scheme.
文摘The haze defects on p-type (111) silicon wafers were investigated by means of chemical etching, Fouriertransform infra-red microscopy (FTIR), spreading resistance measurement. secondary ion mass spectroscopy(SLMS), transmission electron microscopy (TEM) equipped with an energy-dispersive X-ray spectrometer(EDX). The haze defects are the precipitates of silicide of metal impurities (Fe, Ni) on the wafer surface.The formation of haze defects can efficiently be inhibited by utilizing the technology of fast neutronirradiation combined with the internal gettering (IG), and then, the formation and removement mechanismof the haze defects have been discussed in this paper.
