Abstract: A high-resolution spectral image fast acquisition apparatus comprises an illumination source, an objective lens, a beam splitter, a single shot spectral image acquisition assembly and a reference image acquisition assembly, wherein the objective lens is used to align a sample to be measured; the illumination source is used to project an illumination light onto the sample to be measured so that the sample to be measured is amplified by the objective lens; wherein one part of amplified light enters the single shot spectral image acquisition assembly so as to acquire a low-resolution spectral cube of the sample to be measured, and another part of the amplified light enters the reference image acquisition assembly to acquire a high-resolution spectral cube. The apparatus enables rapid access to high-resolution spectral images, thereby speeding up the process of using spectral images for medical diagnosis.

Abstract: An encoded illumination real-time focusing scanning imaging device includes an LED array, an object stage, an objective lens, a liquid lens, a lens sleeve, and a camera. The object stage is used for placing a sample, the LED array is used for emitting bright field light or encoded light, and the bright field light or the encoded light respectively penetrates through the sample and then successively passes through the objective lens, the liquid lens, and the lens sleeve to reach the camera to shoot a bright field image or an encoded light illumination image by the camera. The present invention also discloses an encoded illumination real-time focusing scanning imaging method, which is performed by using the above-mentioned device. The present invention enables fast and accurate focusing at a low cost.

Abstract: The present invention provides a ranging method based on laser-line scanning imaging to effectively suppress interference of extreme weather on imaging. The method includes the following steps: acquiring priori reference images for a fixed laser-line scanning system, including respectively placing reference whiteboards at different distances, projecting line laser beams to the whiteboards, and acquiring the reference images by using a camera; placing a laser-line scanning device in a real scene, causing the laser-line scanning device to respectively emit line lasers at different angles, and acquiring an image at each scanning angle by using a camera; and performing fusion calculation on the acquired scanning image in the real scene and the priori reference images by using a ranging algorithm based on laser-line scanning, and extracting distance information of a surrounding object, to implement environment perception.

Abstract: A high-resolution spectral image fast acquisition apparatus comprises an illumination source, an objective lens, a beam splitter, a single shot spectral image acquisition assembly and a reference image acquisition assembly, wherein the objective lens is used to align a sample to be measured; the illumination source is used to project an illumination light onto the sample to be measured so that the sample to be measured is amplified by the objective lens; wherein one part of amplified light enters the single shot spectral image acquisition assembly so as to acquire a low-resolution spectral cube of the sample to be measured, and another part of the amplified light enters the reference image acquisition assembly to acquire a high-resolution spectral cube. The apparatus enables rapid access to high-resolution spectral images, thereby speeding up the process of using spectral images for medical diagnosis.

Abstract: The present invention provides a ranging method based on laser-line scanning imaging to effectively suppress interference of extreme weather on imaging. The method includes the following steps: acquiring priori reference images for a fixed laser-line scanning system, including respectively placing reference whiteboards at different distances, projecting line laser beams to the whiteboards, and acquiring the reference images by using a camera; placing a laser-line scanning device in a real scene, causing the laser-line scanning device to respectively emit line lasers at different angles, and acquiring an image at each scanning angle by using a camera; and performing fusion calculation on the acquired scanning image in the real scene and the priori reference images by using a ranging algorithm based on laser-line scanning, and extracting distance information of a surrounding object, to implement environment perception.

Abstract: The present invention discloses a depth map super-resolution processing method, including: firstly, respectively acquiring a first original image (S1) and a second original image (S2) and a low resolution depth map (d) of the first original image (S1); secondly, 1) dividing the low resolution depth map (d) into multiple depth image blocks; 2) respectively performing the following processing on the depth image blocks obtained in step 1); 21) performing super-resolution processing on a current block with multiple super-resolution processing methods, to obtain multiple high resolution depth image blocks; 22) obtaining new synthesized image blocks by using an image synthesis technology; 23) upon matching and judgment, determining an ultimate high resolution depth image block; and 3) integrating the high resolution depth image blocks of the depth image blocks into one image according to positions of the depth image blocks in the low resolution depth map (d).

Abstract: A method is provided for computing a predicted frame from a first and a second reference frames, the method comprising, for each block of pixels in the predicted frame, the acts of defining a first block of pixels in the first reference frame collocated with a third block of pixels which is the block of pixels in the predicted frame; defining a second block of pixels corresponding, in the second reference frame, to the first block of pixels along the motion vector of the first block from the first to second reference frames; computing a first set of coefficients allowing the transformation of the pixels of the first block into pixels of the second block; computing pixels of the third block using the first set of coefficients and pixels from a fourth block collocated in the first reference frame with the second block of pixels.

Abstract: The present invention discloses a depth map super-resolution processing method, including: firstly, respectively acquiring a first original image (S1) and a second original image (S2) and a low resolution depth map (d) of the first original image (S1); secondly, 1) dividing the low resolution depth map (d) into multiple depth image blocks; 2) respectively performing the following processing on the depth image blocks obtained in step 1); 21) performing super-resolution processing on a current block with multiple super-resolution processing methods, to obtain multiple high resolution depth image blocks; 22) obtaining new synthesized image blocks by using an image synthesis technology; 23) upon matching and judgment, determining an ultimate high resolution depth image block; and 3) integrating the high resolution depth image blocks of the depth image blocks into one image according to positions of the depth image blocks in the low resolution depth map (d).

Abstract: A method is provided for computing a predicted frame from a first and a second reference frames, the method comprising, for each block of pixels in the predicted frame, the acts of defining a first block of pixels in the first reference frame collocated with a third block of pixels which is the block of pixels in the predicted frame; defining a second block of pixels corresponding, in the second reference frame, to the first block of pixels along the motion vector of the first block from the first to second reference frames; computing a first set of coefficients allowing the transformation of the pixels of the first block into pixels of the second block; computing pixels of the third block using the first set of coefficients and pixels from a fourth block collocated in the first reference frame with the second block of pixels.