A detector's nondestructive readout mode allows its pixels to be read multiple times during integration,enabling generation of a series of"up-the-ramp"images that continuously accumulate photons between ...A detector's nondestructive readout mode allows its pixels to be read multiple times during integration,enabling generation of a series of"up-the-ramp"images that continuously accumulate photons between successive frames.Because noise is correlated across these images,optimal stacking generally requires the images to be weighted unequally to achieve the best possible target signal-to-noise ratio(SNR).Objects in the sky present wildly varied brightness characteristics,and the counts in individual pixels of the same object can also span wide ranges.Therefore,a single set of weights cannot be optimal in all cases.To ensure that the stacked image is easily calibratable,we apply the same weight to all pixels within the same frame.In practice,results for high-SNR cases degraded only slightly when we used weights derived for low-SNR cases,whereas the low-SNR cases remained more sensitive to the weights.Therefore,we propose a quasi-optimal stacking method that maximizes the stacked SNR for the case where the RSN=1 per pixel in the last frame and use simulated data to demonstrate that this approach enhances the SNR more strongly than the equal-weight stacking and ramp fitting methods.Furthermore,we estimate the improvements in the limiting magnitudes for the China Space Station Telescope using the proposed method.When compared with the conventional readout mode,which is equivalent to selecting the last frame from the nondestructive readout,stacking 30 up-the-ramp images can improve the limiting magnitude by approximately 0.5 mag for the telescope's near-infrared observations,effectively reducing readout noise by approximately 62%.展开更多
High-resolution imaging through randomly dynamic scattered fields and highly scattered walls is an extensively sought-after capability with potential applications in various fields such as underwater imaging,biomedica...High-resolution imaging through randomly dynamic scattered fields and highly scattered walls is an extensively sought-after capability with potential applications in various fields such as underwater imaging,biomedical imaging,and seeing through fog.Numerous methods have been proposed to unscramble object information from degraded scattered images,resulting in considerable improvements in image contrast in degraded scenarios[1].展开更多
Multispectral imaging,encompassing a broad spectrum ranging from the visible to the infrared band,plays a pivotal role in various applications,including target identification,compositional analysis,biomedical diagnosi...Multispectral imaging,encompassing a broad spectrum ranging from the visible to the infrared band,plays a pivotal role in various applications,including target identification,compositional analysis,biomedical diagnosis,environmental remote sensing,and many others.展开更多
基金supported by the National Key R&D Program of China (2022YFF0503400)the National Natural Science Foundation of China grant (U1931208)China Manned Space Program through its Space Application System.
文摘A detector's nondestructive readout mode allows its pixels to be read multiple times during integration,enabling generation of a series of"up-the-ramp"images that continuously accumulate photons between successive frames.Because noise is correlated across these images,optimal stacking generally requires the images to be weighted unequally to achieve the best possible target signal-to-noise ratio(SNR).Objects in the sky present wildly varied brightness characteristics,and the counts in individual pixels of the same object can also span wide ranges.Therefore,a single set of weights cannot be optimal in all cases.To ensure that the stacked image is easily calibratable,we apply the same weight to all pixels within the same frame.In practice,results for high-SNR cases degraded only slightly when we used weights derived for low-SNR cases,whereas the low-SNR cases remained more sensitive to the weights.Therefore,we propose a quasi-optimal stacking method that maximizes the stacked SNR for the case where the RSN=1 per pixel in the last frame and use simulated data to demonstrate that this approach enhances the SNR more strongly than the equal-weight stacking and ramp fitting methods.Furthermore,we estimate the improvements in the limiting magnitudes for the China Space Station Telescope using the proposed method.When compared with the conventional readout mode,which is equivalent to selecting the last frame from the nondestructive readout,stacking 30 up-the-ramp images can improve the limiting magnitude by approximately 0.5 mag for the telescope's near-infrared observations,effectively reducing readout noise by approximately 62%.
文摘High-resolution imaging through randomly dynamic scattered fields and highly scattered walls is an extensively sought-after capability with potential applications in various fields such as underwater imaging,biomedical imaging,and seeing through fog.Numerous methods have been proposed to unscramble object information from degraded scattered images,resulting in considerable improvements in image contrast in degraded scenarios[1].
文摘Multispectral imaging,encompassing a broad spectrum ranging from the visible to the infrared band,plays a pivotal role in various applications,including target identification,compositional analysis,biomedical diagnosis,environmental remote sensing,and many others.
