A method for light detection and ranging that includes forming a first light pattern within a region of a scene by holographic projection. The first light pattern includes n light spots arranged in a regular array. A light return signal is received from each light detection element of an array of light detection elements directed at the region of the scene. The intensity of the light return signals is assessed. If the light return signals do not meet at least one signal validation criterion, a second light pattern is formed within the region of the scene by holographic projection. The second light pattern includes m light spots arranged in a regular array, wherein mn. A time-of-flight in association with each light spot of the second light pattern is then determined.

Disclosed is a color implementation property measurement device of holographic images. According to an aspect of the present embodiment, a color implementation property measurement device of a holographic image reproduced by a holographic display device is provided. The color implementation property measurement device includes an optical path adjustment unit configured to adjust the path of each light of different wavelength bands, a light receiver configured to receive and sense a plurality of lights having different wavelength bands, a diffraction element disposed in front of the light receiver in a direction, a rotation element fixed within a predetermined range from the spatial light modulator at one end, and a controller configured to adjust the rotation angle of the rotation element and the distance between the light receiver and the spatial light modulator and analyze the sensed value by the light receiver.

A system for training a machine learning algorithm to generate a plurality of ideal hologram phase correction maps includes a holographic head-up display (HUD) configured to display a plurality of duplicates of a graphic based on a hologram phase map. The system further includes a camera system configured to view each of the plurality of duplicates of the graphic. The system further includes a controller in electrical communication with the holographic HUD and the camera system. The controller is programmed to determine a plurality of ground-truth hologram phase correction maps using a genetic algorithm, the holographic HUD, and the camera system. The controller is further programmed to generate a training dataset including a plurality of images of the graphic and train the machine learning algorithm to generate the plurality of ideal hologram phase correction maps.