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 character segmentation method and apparatus, and a computer-readable storage medium. The character segmentation method comprises: converting a character area image into a grayscale image (step 101); converting the grayscale image into an edge binary image by using an edge detection algorithm (step 102); acquiring character box segmentation blocks from the edge binary image by using a projection method (step 103); and determining a target character area from the character box segmentation blocks by using a contour detection algorithm, and performing character segmentation on the character area image according to the target character area (step 104). Another character segmentation method comprises: converting a character area image into a grayscale image (step 701); performing clustering analysis on the grayscale image by using a fuzzy C-means clustering algorithm, and executing binarization processing on the grayscale image according to a clustering analysis result (step 702); acquiring character positioning blocks from a binary image by using a projection method (step 703); and performing character segmentation on the character area image according to position information of the character positioning blocks (step 704). By using the methods and apparatuses, character segmentation can be performed on a relatively low quality image.

One embodiment provides a method comprising receiving an input content, and receiving ambient contextual data indicative of one or more ambient lighting conditions of an environment including a display device. The input content has corresponding metadata that at least partially represents a creative intent indicative of how the input content is intended to be viewed. The method further comprises adaptively correcting the input content based on the ambient contextual data to preserve the creative intent, and providing the corrected input content to the display device for presentation. The adaptively correcting comprises applying automatic white balancing to the input content to correct color tone of the input content.

The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a progressive refinement network to refine alpha mattes generated utilizing a mask-guided matting neural network. In particular, the disclosed systems can use the matting neural network to process a digital image and a coarse guidance mask to generate alpha mattes at discrete neural network layers. In turn, the disclosed systems can use the progressive refinement network to combine alpha mattes and refine areas of uncertainty. For example, the progressive refinement network can combine a core alpha matte corresponding to more certain core regions of a first alpha matte and a boundary alpha matte corresponding to uncertain boundary regions of a second, higher resolution alpha matte. Based on the combination of the core alpha matte and the boundary alpha matte, the disclosed systems can generate a final alpha matte for use in image matting processes.

An image capturing method and a terminal device are provided. The method includes entering a camera application to start a lens and display a viewfinder interface, converting an original image captured by the lens into a red-green-blue (RGB) image, and decreasing luminance of the RGB image to be less than first luminance or increasing the luminance of the RGB image to be greater than second luminance, to obtain a first image; converting the RGB image into N frames of high-dynamic-range (HDR) images, and fusing color information of pixels in any same location on the first image and the N frames of HDR images to obtain a final 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.

The present disclosure generally relates to a method and device for inverse-tone mapping a picture. The method comprising: —obtaining (20) a first component (Y) comprising: —obtaining a luminance component (L) from said color picture; —obtaining a resulting component by applying (20), a non-linear function on said luminance component (L) in order that the dynamic of the resulting component is increased compared to the dynamic of the luminance component (L)—obtaining (50) a modulation value (Ba) from the luminance of said color picture; —obtaining the first component (Y) by multiplying said resulting component by said modulation value (Ba); —obtaining two chrominance components (C1, C2) from said color picture; —obtaining (40) a first factor (r(L(i))) that depends on the value (L(i)) of a pixel (i) of said luminance component (L); —obtaining (30) at least one color component (Ec) from said first component (Y), said two chrominance components (C1, C2) and said first factor (r(L(i))); and—forming the inverse-tone mapped color picture by combining together said at least one color component (Ec).

For obtaining an good yet easy to use luminance dynamic range conversion, we describe an image color processing apparatus (200) arranged to transform an input color (R,G,B) of a pixel of an input image (Im_in) having a first luminance dynamic range into an output color (Rs, Gs, Bs) of a pixel of an output image (Im_res) having a second luminance dynamic range, which first and second dynamic ranges differ in extent by at least a multiplicative factor 2, comprising: a maximum determining unit (101) arranged to calculate a maximum (M) of color components of the input color, the color components at least comprising a red, green and blue component; —a uniformization unit (201) arranged to apply a function (FP) to the maximum (M) as input, which function has a logarithmic shape and was predetermined to be of a fixed shape enabling to transform a linear input to a more perceptually uniform output variable (u); a function application unit (203) arranged to receive a functional shape of a function, which was specified previously by a human color grader, and apply the function to the uniform output variable (u), yielding a transformed uniform value (TU); a linearization unit (204) arranged to transform the transformed uniform value (TU) to a linear domain value (LU); a multiplication factor determination unit (205) arranged to determine a multiplication factor (a) being equal to the linear domain value (LU) divided by the maximum (M); and a multiplier (104) arranged to multiply at least three linear color components (R,G,B) by the multiplication factor (a), yielding the output color.

A method is disclosed that comprises mapping a high-dynamic range luminance picture to a standard-dynamic range luminance picture based on a backlight value Bac associated with the high-dynamic range luminance picture.

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.