A solution is proposed for assisting a medical procedure. A corresponding method comprises acquiring a luminescence image (205F), based on a luminescence light, and an auxiliary image (205R), based on an auxiliary light different from this luminescence light, of a field of view (103); the field of view (103) contains a region of interest comprising a target body of the medical procedure (containing a luminescence substance) and one or more foreign objects. An auxiliary informative region (210Ri) representative of the region of interest without the foreign objects is identified in the auxiliary image (205R) according to its content, and a luminescence informative region (210Fi) is identified in the luminescence image (205F) according to the auxiliary informative region (210Ri). The luminescence image (205F) is processed limited to the luminescence informative region (210Fi) for facilitating an identification of a representation of the target body therein. A computer program and a corresponding computer program product for implementing the method are also proposed. Moreover, a computing device for performing the method and an imaging system comprising it are proposed. A medical procedure based on the same solution is further proposed.

Computer-implemented image correction for a biomarker test includes a biomarker test which has a calibration array and a biomarker site, wherein the calibration array comprises plural colored patches and the biomarker site is color-responsive to indicate a measurement of biomarkers present. The method comprises: storing a reference color value for each of the plural colored patches; receiving an image of the biomarker test; defining shading of pixels of the image as D, a combination of a plurality of basis functions; defining a color correction matrix, M having parameters that when solved correct color of the calibration array in the image to the corresponding stored values; solving D and M for pixels of the image excluding pixels of the biomarker site; using D and M to interpolate values for pixels of the biomarker site of the image to generate a color and shading corrected image of the biomarker site.

Disclosed are an image dehazing method and system based on CycleGAN. The method comprises: acquiring a to-be-processed hazy image; and inputting the image into a pre-trained densely connected CycleGAN, and outputting a clear image. The densely connected CycleGAN comprises a generator, the generator comprises an encoder, a converter and a decoder, the encoder comprises a densely connected layer for extracting features of an input image, the converter comprises a transition layer for combining the features extracted at the encoder stage, the decoder comprises a densely connected layer and a scaled convolutional neural network layer, the densely connected layer is used for restoring original features of the image, and the scaled convolutional neural network layer is used for removing a checkerboard effect of the restored original features to obtain a finally output clear image.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize a neural network having a long short-term memory encoder-decoder architecture to progressively modify a digital image in accordance with a natural language request. For example, in one or more embodiments, the disclosed systems utilize a language-to-operation decoding cell of a language-to-operation neural network to sequentially determine one or more image-modification operations to perform to modify a digital image in accordance with a natural language request. In some cases, the decoding cell determines an image-modification operation to perform partly based on the previously used image-modification operations. The disclosed systems further utilize the decoding cell to determine one or more operation parameters for each selected image-modification operation. The disclosed systems utilize the image-modification operation(s) and operation parameter(s) to modify the digital image (e.g., by generating one or more modified digital images) via the decoding cell.

Disclosed are an image sensing device and an operating method thereof, and the image sensing device may include: an image sensor including a plurality of pixels and suitable for generating an image based on incident light; and an image processor suitable for generating a high dynamic range (HDR) image based on the image and two or more pieces of tone mapping information, which are divided according to luminance.

Systems and methods herein provide for improving visibility in a scene. In one embodiment, a system includes a first camera device operable to capture images of a scene at a first band of wavelengths, and a second camera device operable to capture images of the scene at a second band of wavelengths. The first and second bands are different. The system also includes a processor communicatively coupled to the first and second camera devices, the processor being operable to detect an object in the scene based on a first of the images from the first camera device and based on a first of the images from the second camera device that was captured at substantially a same time as the first image from the first camera device, to estimate an obscurant in the scene based on the first images, and to estimate a visibility parameter of the scene based on the object and the estimated obscurant.

Methods for improving and modifying a High Dynamic Range (HDR) scene, captured as a series of images of the scene with different exposure levels and the scene through classification-based image merging, tuning, correction, and replacement. The approach employs mixing images to improve the selection and display of both shadowed and highlighted details. The increased efficiency resulting from improvements in computational resource utilization of image processing hardware can, from the implementation of the improved computational methods herein, significantly reduce the time required to generate and display a tone-mapped HDR image, a gamma-corrected HDR image, and/or a segmented and replaced HDR image.

To enable better color and in particular color saturation control for HDR image handling systems which need to do luminance dynamic range conversion, e.g. from a SDR image to an image optimized for rendering on a display of higher display peak brightness and dynamic range, the inventors invented an apparatus (400) for processing a color saturation (C′bL, C′rL) of an input color (Y′L, C′bL, C′rL) of an input image (Im_RLDR) to yield an output color (Y′M, Cb′M, Cr′M) of an output image (Im3000nit) corresponding to the input image, which output image is a re-grading of the input image characterized by the fact that its pixel colors have a different normalized luminance position (Y2) compared to the normalized luminance positions of the input colors (Y1), the normalized luminances being defined as the luminance of a pixel divided by the respective maximal codeable luminance of the image's luminance representation, whereby the ratio of the maximum codeable luminance of the input image and the maximum codeable luminance of the output image is at least 4 or larger, or ¼.sup.th or smaller, the apparatus comprising: a receiver (206) arranged to receive a luminance mapping function (F_L_s2h) defining a mapping between the luminance of the input color (Y′L) and a reference luminance (L′_HDR), and an initial saturation processing function (F_sat) defining saturation boost values (b) for different values of the luminance of the input color (Y′L); a display tuning unit (1009) arranged to calculate a display tuned luminance mapping function (F_L_da) based on the luminance mapping function (F_L_s2h) and at least one of a display peak brightness (PB_D) and a minimum discernable black (MB_D); a luminance processor (401) arranged to apply the display tuned luminance mapping function (F_L_da) to determine an output luminance (Y′M) from the input luminance (Y′L) of the input color; and a saturation processing unit (410, 411), arranged to map the input color saturation (C′bL, C′rL) to the color saturation (Cb′M, Cr′M) of the output color on the basis of a saturation processing strategy which specifies saturation multipliers for the normalized luminance values (Y_norm); characterized in that the apparatus further comprises a saturation factor determination unit (402) arranged to calculate a final saturation processing strategy (b; Bcorr) based on the initial saturation processing strategy (F_sat) and based on a secondary luminance value (Y′_H) which is derivable from the output luminance (Y′M) by applying a luminance mapping function (F_M2H) based on the luminance mapping function (F_L_s2h), and whe

An image processing apparatus includes a hardware processor configured to: acquire a plurality of pieces of image information including image-capturing regions overlapping partially; to set first and second correction values with a predetermined value, the first correction value being used for correction of luminance of a first region of interest included in a first overlap region in which a first image-capturing region overlaps an adjacent second image-capturing region, the second correction value being used for correction of luminance of a second region of interest included in a second overlap region in which the first image-capturing region overlaps an adjacent third image-capturing region; and to set with the first and second correction values an individual correction value used for correction of luminance of a region between the first region of interest and the second region of interest in the first image-capturing region.

An image processing apparatus comprises a changing unit configured to change a display area of an image from a first display area to a second display area including at least a portion of the first display area, an acquiring unit configured to acquire a first value indicating luminance, in which brightness contrast is considered, in an image displayed in the first display area and a second value indicating luminance, in which brightness contrast is considered, in an image displayed in the second display area, and a correcting unit configured to correct luminance of the image displayed in the second display area based on the first value and the second value that are acquired by the acquiring unit.