Intel Corporation

Aleksandar Sutic

Gilad Michael

Zoran Zivkovic

Jun Nishimura

Aleksandar Beric

Chyuan-Tyng Wu

Timo Gerasimow

Sushma Rao

Vladimir Kovacevic

Ivan Micovic

Visnja Krsmanovic

Dusan Stevanovic

Marko Sredic

Pavle Petrovic

Dalibor Segan

In an example method for training image signal processors, a reconstructed image is generated via an image signal processor based on a sensor image. An intermediate loss function is generated based on a comparison of an output of one or more corresponding layers of a computer vision network and a copy of the computer vision network. The output of the computer vision network is based on the reconstructed image. An image signal processor is trained based on the intermediate loss function.

Training image signal processors using intermediate loss functions

A mechanism is described for facilitating hybrid tone mapping in camera systems according to one embodiment. A method of embodiments, as described herein, includes detecting a scene having a sequence of frames, and fusing the sequence of frames into a fused raw frame. The method may further include reconstructing the scene by performing global tone mapping and local tone mapping on the fused raw frame, and outputting an image reflecting the reconstructed scene based on the tone-mapped raw frame.

Hybrid tone mapping for consistent tone reproduction of scenes in camera systems

A mechanism is described for facilitating automatic tuning of image signal processors using reference images in image processing environments, according to one embodiment. A method of embodiments, as described herein, includes one or more processors to: receive images associated with one or more scenes captured by one or more cameras; access tuning parameters associated with functionalities within an image signal processor (ISP) pipeline; generate reference images based on the tuning parameters, wherein a reference image is associated with an image for each functionality within the ISP pipeline; and automatically tune the ISP pipeline based on selection of one or more of the reference images for one or more of the images for one or more of the functionalities.

Automatic tuning of image signal processors using reference images in image processing environments

High dynamic range image composition is described using multiple images. Some embodiments relate to a system with a buffer to receive each of three different images of a scene, each image having a different amount of light exposure to the scene, as general purpose processor to estimate the alignment between the three images, and an imaging processor to warp the images based on the estimated alignment and to combine the three images to produce a single high dynamic range image.

High dynamic range image composition using multiple images

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Santa Clara, CA, United States of America

Aleksandar Sutic