Infrared scattering scanning near-field optical microscopy (IR s-SNOM) provides for spectroscopic imaging with nanometer spatial resolution, yet full spatio-spectral imaging is constrained by long measurement times. Here, we demonstrate the application of compressed sensing algorithms to achieve hyperspectral FTIR-based nano-imaging at an order of magnitude faster imaging speed to achieve the same spectral content compared to conventional approaches. At the example of the spectroscopy of a single vibrational resonance, we discuss the relationship of prior knowledge of sparseness of the employed Fourier base functions and sub-sampling. Compressed sensing nano-FTIR spectroscopy promises both rapid and sensitive chemical nano-imaging which is highly relevant in academic and industrial settings for fundamental and applied nano- and bio-materials research.

Compressed sensing FTIR nano-spectroscopy and nano-imaging.

The embodiment of the invention discloses an image compression and detail enhancement method for an infrared image. The image compression and detail enhancement method for the infrared image comprises the following steps: obtaining an original infrared image; decomposing the original infrared image into a base map partial image and a detail partial image; carrying out dynamic range compression on the base map partial image to obtain a compression base map partial image; removing stripe noise in the detail partial image, and carrying out detail enhancement processing to obtain an enhanced detail partial image; and combining the compression base map partial image with the enhanced detail partial image. According to the image compression and detail enhancement method for the infrared image, which is disclosed by the embodiment of the invention, the scene information of a global big dynamic range is reasonably compressed, meanwhile, the detail information of a global small dynamic target is enhanced on the basis of effectively inhibiting the stripe noise, the big dynamic range of the infrared image is compressed, the detail information of the infrared image is kept, and the integral display effect of the image is obviously improved.

Image compression and detail enhancement method for infrared image

The invention discloses a low-light-level image enhancement algorithm based on a parabolic function to overcome the defects that an existing low-light-level image enhancement algorithm is large in calculated amount, the color distortion is serious, and the contrast ratio is low According to the algorithm, firstly, the illumination situation of an image is measured according to the distribution situation of a histogram; secondly, segmented parabolic functions with different parameters are adopted for images with different illumination classifications to carry out the self-adaptation illumination enhancement; thirdly, equivalent-ratio enhancement is carried out on RGB channels, the colors are kept unchangeable, and a primary enhancement image is obtained; to increase the speed, the image is converted to the YUV color space, only the luminance component Y is denoised through guiding filtering, and the RBG color space is restored; lastly, detail compensation is carried out on the filtered image to obtain the final enhancement image According to the method, the visual effect can be effectively improved without losing the image information, and the effect is superior to the effect of other methods According to the method, the enhancement effect on the low-light-level image is obvious, the processing speed is high, and the high practicality is achieved

Low-light-level image enhancement algorithm based on parabolic function

The invention discloses a high dynamic infrared image enhancement method based on multi-scale processing. Firstly, a weight least square filter is applied to carry out edge preserving type image multi-scale hierarchical operation on an original image, then the respective obtained multi-layer detail image and residual fuzzy image are processed, thus the detail is amplified appropriately, a residual layer is compressed, finally a plurality of detail layers and the residual layer are combined, and a low dynamic range image for display is obtained. According to the method, infrared image details can be reserved well, and halo and gradient reversal phenomena in a synthetic image caused by a detail separation operation are avoided or weakened at the same time.

High dynamic infrared image enhancement method based on multi-scale processing

The invention provides an infrared small target detection method and system based on an FPGA Acquired images are preprocessed to be denoised and processed through blind pixel removal; a head image and a tail image are extracted; clutter edge filtering operation is carried out on the head image and the tail image; threshold segmentation operation is carried out on the head image and the tail image so that the images can be binary ; morphological expansion is carried out on the target in the head image processed through threshold segmentation and the target in the tail image processed through threshold segmentation, and targets with large contours are obtained; the head target processed through morphological expansion and the tail target processed through morphological expansion are synthesized so that a complete target can be obtained According to the infrared small target detection method and system based on the FPGA, the signal-to-noise ratio can be increased by accumulating the superposition portions of a previous frame and a next frame, the interference of a background cloud layer can be well removed while the algorithm complexity is reduced, and the real time performance of the detection system can be improved while accuracy is guaranteed

Infrared small target detection method and system based on FPGA

The invention discloses an FPGA (field programmable gate array)-based infrared image detail enhancing system and method. The system comprises a bilateral filtering module, a gaussian filtering module, a histogram projecting module and an automatic gain control module, wherein the bilateral filtering module is connected with the gaussian filtering module which is connected with the histogram projecting module and the automatic gain control module respectively, and original input data firstly passes through the bilateral filtering module to obtain image pattern fundamental frequency information; the fundamental frequency information passes through the gaussian filtering module to be smoothened, and differencing is carried out between a result and the original input data so as to obtain image detail information; and the detail information is amplified by the automatic gain control module, the fundamental frequency information is compressed by the histogram projecting module, and the detail information and the fundamental frequency information are summed to obtain an output image. According to the invention, the contrast ratio of the image can be improved, the detail information can be enhanced, background noise can be restrained, and the common problems that the edge is fuzzy and a visual effect is poor in the image of a thermal infrared imager imaging system in the prior art can be solved.

FPGA (field programmable gate array)-based infrared image detail enhancing system and method

The invention discloses an inter-frame noise reduction method based on motion detection According to the method, moving targets are extracted by a multi-Gaussian mixture background model method and an overlapping stationary area between two adjacent frames are found, then inter-frame accumulative filtering is performed on the area, and moving target areas and non-moving target areas in non-overlapping areas are replaced by background models established by an intra-frame filtering algorithm and the multi-Gaussian mixture background model method respectively Meanwhile, the algorithm can also self-adaptively adjust the number of stack frames and has a multistage adjustable function The innovative points reside in that moving target detection of images is performed firstly, then AND operation is performed on two successive frames of foreground images including the moving targets only, and the inter-frame filtering algorithm, the intra-frame filtering algorithm or a background model replacement algorithm is selected according to the result of AND operation so that the phenomena of edge virtual images, pseudo images and even lost of the moving targets caused by the conventional inter-frame filtering algorithm can be avoided, and the great noise reduction effect of the moving images can also be achieved

Inter-frame noise reduction method based on motion detection

Infrared super-resolution imaging based on compressed sensing

The invention discloses a high-speed high-definition CMOS imaging system. The system comprises a lens, a CMOS camera and a computer. The CMOS camera comprises a power supply unit, a CMOS sensor chip, a FPGA control unit, a high speed data memory cell, a CameraLink interface unit, a parameter memory cell and an upper computer interface unit. Through using a high-speed high-definition CMOS chip, a 1280*1024 resolution of the CMOS camera is realized; through using a DDR3 high speed image memory cell, high speed image data is stored in real time, a storage capacity is increased, a data transmission bandwidth is increased too, and during the 1280*1024 resolution, a work speed whose frame frequency is 1000 frame/second is realized; through using a DC-DC power supply and a LDO power supply to provide power, a system noise is small, power consumption is low and imaging quality is good; and through using a CameraLink interface to transmit image data, real-time image display below 400 frame/second (the resolution is 1280*1024) can be realized, and a high-speed high-definition shooting requirement is satisfied. Besides, the system can configure parameters of a work mode and the like of a CMOS detector through an upper computer, and usage is simple and convenient.

High-speed high-definition CMOS imaging system

The invention discloses a non-uniformity correction method of a non-barrier infrared thermal imaging system. The method comprises the steps of: dividing a substrate temperature into M intervals according to a substrate temperature range, shooting black bodies of different temperatures in each temperature interval, dividing original output of a detector into N intervals, calibrating M*N frames of images, and storing the images; then, according to the substrate temperature, reading the calibrated M frames of images above and below the substrate temperature by the detector; and subsequently, according to a response value of each pixel point, determining corresponding values of two temperature curves above and below the substrate temperature, carrying out weighted calculation based on the substrate temperature, and obtaining a final output value. According to the invention, barriers are successfully removed in interval division of the substrate temperature in the calibration process, the non-uniformity caused by output non-linearity of the detector is also considered, and interval division is also carried out the original output of the detector, so that secondary calibration is not needed after all images are calibrated, a once for all effect is achieved, and the influences of non-uniformity caused by the non-linearity of the infrared detector are also solved.

Shen Xuewei

Papers

FPGA (field programmable gate array)-based infrared image detail enhancing system and method

Inter-frame noise reduction method based on motion detection

Infrared super-resolution imaging based on compressed sensing

High-speed high-definition CMOS imaging system

Non-uniformity correction method of non-barrier infrared thermal imaging system