An apparatus includes at least one processing device configured to obtain an input image and determine a cumulative distribution function (CDF) histogram from a luminance or luma (Y) channel of the input image. The at least one processing device is also configured to determine an entry CDF histogram in a CDF histogram lookup table (LUT) closest to the determined CDF histogram. The at least one processing device is further configured to apply a Y channel global tone mapping (GTM) curve to the input image based on one or more parameters assigned to the entry CDF histogram from the CDF histogram LUT.

An apparatus includes at least one processing device configured to obtain an input image and determine a cumulative distribution function (CDF) histogram from a luminance or luma (Y) channel of the input image. The at least one processing device is also configured to determine an entry CDF histogram in a CDF histogram lookup table (LUT) closest to the determined CDF histogram. The at least one processing device is further configured to apply a Y channel global tone mapping (GTM) curve to the input image based on one or more parameters assigned to the entry CDF histogram from the CDF histogram LUT.

An image processing apparatus includes a processor configured to extract a component related to luminance of each of a sample image and a processing target image that is to undergo image processing to match an impression of the processing target image to the sample image, extract feature values of the processing target image and the sample image by attaching to a pixel value of each pixel forming the processing target image and the sample image a weight responsive to the component related to the luminance, and make adjustment to match the feature value of the processing target image to the feature value of the sample image.

A mapping curve parameter obtaining method and apparatus are described. The method includes obtaining a first mapping curve parameter set and first maximum target system display luminance, and obtaining a display luminance parameter set, where the display luminance parameter set includes maximum display luminance and/or minimum display luminance of a display device. The method also includes obtaining an adjustment coefficient set, where the adjustment coefficient set includes one or more adjustment coefficients, and the one or more adjustment coefficients correspond to one or more parameters in the first mapping curve parameter set. Furthermore, the method includes adjusting the one or more parameters in the first mapping curve parameter set based on the display luminance parameter set, the first maximum target system display luminance, and the adjustment coefficient set to obtain a second mapping curve parameter set, where the second mapping curve parameter set includes one or more adjusted parameters.

A method and apparatus may be used for performing a scene-based automatic white balance correction. The method may include obtaining an input image. The method may include obtaining a raw image thumbnail. The method may include obtaining an augmented image thumbnail. The method may include computing a histogram from an image thumbnail. The method may include determining a scene classification. The method may include learning a filter. The filter may be learned from one or several different instances of the raw image thumbnail, the augmented image thumbnail, the scene classification, or any combination thereof. The method may include applying the filter to the histogram to determine white balance correction coefficients and obtain a processed image.

A method and apparatus may be used for performing a scene-based automatic white balance correction. The method may include obtaining an input image. The method may include obtaining a raw image thumbnail. The method may include obtaining an augmented image thumbnail. The method may include computing a histogram from an image thumbnail. The method may include determining a scene classification. The method may include learning a filter. The filter may be learned from one or several different instances of the raw image thumbnail, the augmented image thumbnail, the scene classification, or any combination thereof. The method may include applying the filter to the histogram to determine white balance correction coefficients and obtain a processed image.

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 real-time video enhancement method performed at a terminal includes: obtaining an average luminance of a current frame of an image; in accordance with a determination that the average luminance is less than the luminance threshold: obtaining a pixel range of an area of interest of the current frame; determining a local enhancement curve of the current frame according to the pixel range of the area of interest of the current frame; determining a first enhancement curve corresponding to the current frame according to the average luminance of the current frame; determining a second enhancement curve of the current frame according to the local enhancement curve of the current frame and the first enhancement curve of the current frame; and adjusting the current frame according to the second enhancement curve.

A real-time video enhancement method performed at a terminal includes: obtaining an average luminance of a current frame of an image; in accordance with a determination that the average luminance is less than the luminance threshold: obtaining a pixel range of an area of interest of the current frame; determining a local enhancement curve of the current frame according to the pixel range of the area of interest of the current frame; determining a first enhancement curve corresponding to the current frame according to the average luminance of the current frame; determining a second enhancement curve of the current frame according to the local enhancement curve of the current frame and the first enhancement curve of the current frame; and adjusting the current frame according to the second enhancement curve.

In a system for coding high dynamic range (HDR) images using lower-dynamic range (LDR) images, a reshaping function allows for a more efficient distribution of the codewords in the lower dynamic range images for improved compression. A trim pass of the LDR images by a colorist may satisfy a director's intent for a given “look,” but may also result in unpleasant clipping artifacts in the reconstructed HDR images. Given an original forward reshaping function which maps HDR luminance values to LDR pixel values, a processor identifies areas of potential clipping and generates modified forward and backward reshaping functions to reduce the visibility of potential artifacts from the trim pass process while preserving the director's intent.