A method of generating a depth image includes irradiating an object with a light which is generated from a light source, acquiring a plurality of phase difference signals which have different phase differences from one another, by sensing a reflection light reflected from the object, generating a first depth image based on the plurality of phase difference signals, generating a second depth image based on phase difference signals in which a motion artifact has not occurred, among the plurality of phase difference signals, generating a third depth image by combining the first depth image and the second depth image.

Systems and methods are disclosed herein for determining a diagnosis based on a base skin tone of a patient. In an embodiment, the system receives a base skin tone image of a patient, generates a calibrated base skin tone image by calibrating the base skin tone image using a reference calibration profile, and determines a base skin tone of the patient based on the calibrated base skin tone image. The system receives a concern image of a portion of the patient's skin, and selects a set of machine learning diagnostic models from a plurality of sets of candidate machine learning diagnostic models based on the base skin tone of the patient, each of the sets of candidate machine learning diagnostic models trained to receive the concern image and output a diagnosis of a condition of the patient.

A method for training a neural network to perform assessments of image quality is provided. The method includes: inputting into the neural network at least one set of images, each set including an image and at least one degraded version of the image; performing comparative ranking of each image in the at least one set of images; and training the neural network with the ranking information. A neural network and image signal processing tuning system are disclosed.

A processor for signal reshaping receives an input image with an input bit depth. Block-based standard deviations are computed. The input codewords are divided into codeword bins and each bin is assigned a standard deviation value. For each bin, a standard deviation to bit-depth function is applied to the bin values to generate minimal bit depth values for each codeword bin. An output codeword mapping function is generated based on the input bit depth, a target bit depth, and the minimal bit depth values. The codeword mapping function is applied to the input image to generate an output image in the target bit depth.

An image processor includes a curve generator and a gradation correcting unit. Based on a predetermined correspondence relationship between average luminance of an image and a gradation correction curve, the curve generator generates, in accordance with average luminance of an input image, a common curve, i.e. a gradation correction curve used to correct a gradation of the input image. The gradation correcting unit uses in common the common curve generated by the curve generator for red, green, and blue color signals of the input image to correct gradations of the red, green, and blue color signals. Based on first average luminance, i.e. an average value of luminance of a first region in the input image, second average luminance, i.e. an average value of luminance of a predetermined-colored second region included in the first region, and an area of the second region, the curve generator generates a common curve.

Techniques and systems are described for mapping 360-degree video data to a truncated square pyramid shape. A 360-degree video frame can include 360-degrees' worth of pixel data, and thus be spherical in shape. By mapping the spherical video data to the planes provided by a truncated square pyramid, the total size of the 360-degree video frame can be reduced. The planes of the truncated square pyramid can be oriented such that the base of the truncated square pyramid represents a front view and the top of the truncated square pyramid represents a back view. In this way, the front view can be captured at full resolution, the back view can be captured at reduced resolution, and the left, right, up, and bottom views can be captured at decreasing resolutions. Frame packing structures can also be defined for 360-degree video data that has been mapped to a truncated square pyramid shape.

An image correction method includes: obtaining information regarding at least one of brightness and colors of pixels constituting an input image, the input image comprising a plurality of regions classified according to whether the at least one of the brightness and the colors of the pixels are substantially uniformly distributed in a corresponding region; determining a weight with respect to at least one pixel based on the obtained information; and correcting the input image with respect to the at least one pixel based on the determined weight.

A method for generating and employing a camera noise model, performed by a processing unit, is introduced to at least contain the following steps. A first frame is obtained by controlling a camera module via a camera module controller. A camera noise model is generated on-line according to the content of the first frame, which describes relationships between pixel values and standard deviations. A second frame is obtained by controlling the camera module via the camera module controller. The content of the second frame is adjusted using the camera noise model, and the second frame, which has been adjusted, is stored in a frame buffer.

A dynamic analysis apparatus may include a setting section which sets a target region in a lung region of a chest dynamic image; a conversion section which calculates a representative value of a pixel signal value in the target region, and converts the pixel signal value; an extraction section which extracts a pulmonary blood flow signal from the image; and a calculation section which calculates a change in the pulmonary blood flow signal, and calculates a feature amount regarding pulmonary blood flow. The setting section may determine a size of the target region based on a size of a body part other than a lung blood vessel, a movement amount of a body part other than the lung blood vessel or subject information of the chest dynamic image, the subject information regarding a subject of the radiation imaging, and the setting section may set the target region.

A video analysis system includes: a video data acquiring means that acquires video data; a moving object detecting means that detects a moving object from video data acquired by the video data acquiring means, by using a moving object detection parameter, which is a parameter for detecting a moving object; an environment information collecting means that collects environment information representing an external environment of a place where the video data acquiring means is installed; and a parameter changing means that changes the moving object detection parameter used when the moving object detecting means detects a moving object, on the basis of the environment information collected by the environment information collecting means.