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.

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.

An object having a high attention degree is selected from objects detected by a detection means, brightness of a captured image is calculated by using an attention region corresponding to the selected object as a detection frame, and exposure control is performed based on the calculated brightness. The attention degree is evaluated higher with the decrease in the distance. Alternatively, the attention degree is evaluated higher as the direction becomes closer to the traveling direction. The attention region is made larger with the decrease in the distance to the object. It is also possible to judge the type of the object and determine the size of the attention region based on the result of the judgment. A subject to be paid attention to is made clearly visible.

A method for spatially-adaptive tone mapping in an image having high dynamic range includes using a computing device to receive an input image from an image sensor comprising a plurality of pixels having pixel locations and determine within the input image a plurality of local size scales, each comprising a neighborhood having substantially constant illumination. The variation in reflectance within each neighborhood is estimated and local contrast within each neighborhood is enhanced. Using the illumination and variation within the contrast-enhanced neighborhoods, the image is remapped to a reduced dynamic range to generate an output image.

Image frames for computational photography may be corrected, such as through rolling shutter correction (RSC), prior to fusion of the image frames to reduce wobble and jitter artifacts present in a video sequence of HDR-enhanced image frames. First and second motion data regarding motion of the image capture device may be determined for times corresponding to the capturing of the first and second image frames, respectively. The rolling shutter correction (RSC) may be applied to the first and second image frames based on both the first and second motion data. The corrected first and second image frames may then be aligned and fused to obtain a single output image frame with higher dynamic range than either of the first or second image frames.

An example apparatus for compressing dynamic range includes an image receiver to receive an input image with a high dynamic range. The apparatus further includes a darkness gamma transfer calculator to calculate gain values for each output pixel via a darkness gamma transfer function. The apparatus also further includes a gain applicator to apply the gain values to color channel values of the input image to generate a compressed image.

An image processing device is disclosed. The image processing device includes at least one first pixel having a first sensitivity, a second pixel having a second sensitivity different from the first sensitivity, a processor, and a synthesizer. The processor calculates a sampling position of the at least one first pixel and a sampling position of the second pixel, determines a reference position and adjusts the sampling position of the at least one first pixel or the second pixel based on the reference position.

A method and apparatus analyze a difference of at least two gradings of an image on the basis of: obtaining a first graded picture (LDR) with a first luminance dynamic range; obtaining data encoding a grading of a second graded picture (HDR) with a second luminance dynamic range, different from the first luminance dynamic range; and determining a grading difference data structure (DATGRAD) on the basis of at least the data encoding the grading of the second graded picture (HDR), which allows more intelligently adaptive encoding of the imaged scenes, and consequently also better use of those pictures, such as higher quality rendering under various rendering scenarios.

An apparatus for recognizing an object in an image includes a preprocessing module configured to receive an image including an object and to output a preprocessed image by performing image enhancement processing on the received image to improve a recognition rate of the object included in the received image; and an object recognition module configured to recognize the object included in the image by inputting the preprocessed image to an input layer of an artificial neural network for object recognition.