Research On Random Broad-band Coded-illumination Multispectral Imaging

The spectral imaging technology can obtain the image of the target scene,and can also obtain continuous,smooth spectral curve that reflects the characteristics of the target scene.Among many multispectral imaging techniques,the systems using LED illumination and a monochrome camera have been widely applied in medical diagnostics and object detection,due to their simple structure and low cost.Current multispectral imaging systems based on LED illumination mostly use multiple spectrally distinct LEDs and need multiple exposures.The spectral distribution of each LED is a Gaussian-like function,which makes the number of bands of the spectral image limited by the number of LEDs and results in poor information collection capability in spectral dimensions.Recently,the compressive sensing theory brought new opportunities for spectral imaging technology.The computational imaging technology based on the compressive sensing theory has been developed rapidly,such as single pixel camera,coded aperture snapshot spectral imager,etc.In this paper,we proposed a multispectral imaging method using random broadband coded-illumination.The proposed method divides the spectral imaging process into two stages:the observation process and the data restoration process.First,the target scene is coded with aliased sampling.Then the high-resolution spectral image is obtained with an optimized algorithm.In the observation process,no longer a single type of LED but several types of LED are randomly coded and combined for light sampling.Simulation result shows that the proposed framework has higher PSNR and spectral accuracy with fewer exposures than traditional methods.To further verify the feasibility of our method,this paper also sets up a hardware system platform,and the experimental results verified the effectiveness of the method.