6 results about "Reflectance map" patented technology

A method for performing point-to-point whiteboard parameter ratio correction on a hyperspectral image includes: capturing hyperspectral data of a standard reference whiteboard in advance as white(x,y,w), and storing the records, then captures hyperspectral data of a sample as sample(x,y,w); then selecting an unobstructed and unshaded whiteboard area within a certain range of the hyperspectral data sample(x,y,w) of the test sample, and labeling the area as Area A; calculating a spectral average of the ROI on the sample image as SA(w); calculating a spectral average of whiteboard data in the same position as the ROI as WA(w); dividing the two spectral averages, and obtaining a correction coefficient alpha(w)=WA(w). / SA(w); multiplying the whiteboard parameter ratio correction coefficient alpha(w) by a sample reflectance image matrix after whiteboard parameter ratio correction to obtain a final hyperspectral reflectance image matrix REFL(x,y,w)=alpha(w).*sample(x,y,w). / white(x,y,w).

The application discloses a satellite remote sensing data collection and preprocessing method and system, and relates to the technical field of satellite navigation. The method specifically comprises the following steps: collecting remote sensing images of a semiarid region through a satellite, analyzing pixel radiation and brightness gradient to identify bare land water features, constructing a leading atlas, extracting a boundary and registering to generate a standard structure, combining a climate model to correct to generate a reflectivity layer, transferring instructions when parameters are insufficient, reconstructing a queue by using a shortest algorithm to complete radiation calibration, atmospheric correction and geometric registration, and forming a preprocessing layer set. In the application, multi-band division is combined with radiation gradient calculation to enhance the separation degree of ground objects, boundary feature extraction and geometric registration are used to eliminate imaging distortion, a dynamic radiation model is fused with climate parameters to correct reflectivity, a double-threshold value is monitored to optimize a transmission strategy and avoid interruption, a priority algorithm is used to reconstruct a queue to reduce data delay, multi-level quality control is used to cooperatively process to form standard data, and the temporal and spatial reliability and application value are improved.

The present application relates to the field of image processing and computer vision, and discloses an unsupervised low-light image enhancement method and system, the method comprising the following steps: S1, constructing a diffusion model; S2, training the diffusion model using pairs of low-quality images in a public dataset and the sum of four loss functions; S3, training the diffusion model using any non-paired low-light image, normal-light image and the sum of two loss functions; S4, using the reflectance map of the low-light feature and the illumination map of the normal-light feature as the diffusion model, and under the guidance of the low-light feature, the enhanced feature is obtained by restoration, and the enhanced feature is used as the input of the decoder to reconstruct the final enhanced image. The system comprises a model construction unit, a model training unit and an enhanced image output unit. The present application also discloses an electronic device and a computer readable storage medium. The present application is used for low-light image enhancement by using traditional retinal theory and deep neural network.

A light-emitting display device according to one or more embodiments of the present invention may include: a substrate comprising a plurality of sub-pixels, the plurality of sub-pixels having light-emitting regions and non-light-emitting regions; data lines and gate lines disposed in the non-light-emitting regions on the substrate and intersecting each other; at least one insulating layer disposed on the data lines and the gate lines; and a color filter disposed on the at least one insulating layer and corresponding to at least one sub-pixel of the plurality of sub-pixels, wherein one or more of the plurality of sub-pixels may include a low-reflectivity pattern overlapping the light-emitting regions.

Provided in the present application are an image processing method and apparatus, and an agent. The method relates to the field of image processing, and comprises: on the basis of a vision sensor, acquiring original images of a physical environment where the vision sensor is located; and on the basis of the original images, obtaining reflectance maps, wherein the reflectance maps are used for determining pose and motion parameters of the vision sensor. By means of processing the reflectance maps that can reflect intrinsic properties of an environmental object, the impact of non-ideal lighting conditions can be reduced, such that the calculated pose and motion parameters of the vision sensor are more accurate.