Methods and apparatuses are disclosed herein for performing tone mapping and/or contrast enhancement. In some examples, a block mapping curve is low-pass filtered with block mapping curves of surrounding blocks to form a smoothed block mapping curve. In some examples, overlapped curve mapping of block mapping curves, including smoothed block mapping curves, is performed, including weighting, based on a pixel location, block mapping curves of a group of blocks to generate an interpolated block mapping curve and applying the interpolated block mapping curve to a pixel to perform ton mapping and/or contrast enhancement.

Methods and apparatuses are disclosed herein for performing tone mapping and/or contrast enhancement. In some examples, a block mapping curve is low-pass filtered with block mapping curves of surrounding blocks to form a smoothed block mapping curve. In some examples, overlapped curve mapping of block mapping curves, including smoothed block mapping curves, is performed, including weighting, based on a pixel location, block mapping curves of a group of blocks to generate an interpolated block mapping curve and applying the interpolated block mapping curve to a pixel to perform ton mapping and/or contrast enhancement.

An endoscopic camera device having an optical assembly; a first image sensor in optical communication with the optical assembly, the first image sensor receiving a first exposure and transmitting a first low dynamic range image; a second image sensor in optical communication with the optical assembly, the second image sensor receiving a second exposure and transmitting a second low dynamic range image, the second exposure being higher than the first exposure; and a processor for receiving the first low dynamic range image and the second low dynamic range image; wherein the processor is configured to combine the first low dynamic range image and the second dynamic range image into a high dynamic range image using a luminosity value derived as a preselected percentage of a cumulative luminosity distribution of at least one of the first low dynamic range image and the second low dynamic range image.

A method of generating and optimizing a codebooks for document analysis comprises: receiving a first set of document images; extracting a plurality of keypoint regions from each document image of the first set of document images; calculating local descriptors for each keypoint region of the extracted keypoint regions; clustering the local descriptors such that each center of a cluster of local descriptors corresponds to a respective visual word; generating a codebook containing a set of visual words; and optimizing the codebook by maximizing mutual information (MI) between a target field of a second set of document images and at least one visual word of the set of visual words.

A method of generating and optimizing a codebooks for document analysis comprises: receiving a first set of document images; extracting a plurality of keypoint regions from each document image of the first set of document images; calculating local descriptors for each keypoint region of the extracted keypoint regions; clustering the local descriptors such that each center of a cluster of local descriptors corresponds to a respective visual word; generating a codebook containing a set of visual words; and optimizing the codebook by maximizing mutual information (MI) between a target field of a second set of document images and at least one visual word of the set of visual words.

An image processing method is provided. In the method, a target video frame set is acquired from video data of a plurality of video frames. The target video frame set includes a subset of the video frames that is selected based on characteristics of the subset of the video frames. A global color feature of a reference video frame is acquired. An image semantic feature of the reference video frame is acquired. An enhancement parameter of the reference video frame is acquired for each of at least one image information dimension according to the global color feature and the image semantic feature. Image enhancement is separately performed on the video frames in the target video frame set according to each enhancement parameter of the reference video frame to obtain target image data for each of the video frames in the target video frame set.

An image processing method is provided. In the method, a target video frame set is acquired from video data of a plurality of video frames. The target video frame set includes a subset of the video frames that is selected based on characteristics of the subset of the video frames. A global color feature of a reference video frame is acquired. An image semantic feature of the reference video frame is acquired. An enhancement parameter of the reference video frame is acquired for each of at least one image information dimension according to the global color feature and the image semantic feature. Image enhancement is separately performed on the video frames in the target video frame set according to each enhancement parameter of the reference video frame to obtain target image data for each of the video frames in the target video frame set.

An imaging apparatus amplifies signal voltage resulting from voltage conversion of signal charge obtained by photoelectric conversion of an optical image of an object and then performs digital conversion to the signal voltage. The imaging apparatus includes an amplifier circuit that amplifies the signal voltage using two or more amplification factors that are set, a weight determining unit configured to determine weights for the respective signals subjected to the digital conversion after the amplification based on the two or more amplification factors, and a combining unit configured to combine the two or more signals subjected to the digital conversion after the amplification using the weights.

An imaging apparatus amplifies signal voltage resulting from voltage conversion of signal charge obtained by photoelectric conversion of an optical image of an object and then performs digital conversion to the signal voltage. The imaging apparatus includes an amplifier circuit that amplifies the signal voltage using two or more amplification factors that are set, a weight determining unit configured to determine weights for the respective signals subjected to the digital conversion after the amplification based on the two or more amplification factors, and a combining unit configured to combine the two or more signals subjected to the digital conversion after the amplification using the weights.

The current document is directed to digital-image-normalization methods and systems that generate accurate intensity mappings between the intensities in two digital images. The intensity mapping generated from two digital images is used to normalize or adjust the intensities in one image in order to produce a pair of normalized digital images to which various types of change-detection methodologies can be applied in order to extract differential data. Accurate intensity mappings facilitate accurate and robust normalization of sets of multiple digital images which, in turn, facilitates many additional types of operations carried out on sets of multiple normalized digital images, including change detection, quantitative enhancement, synthetic enhancement, and additional types of digital-image processing, including processing to remove artifacts and noise from digital images.