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Chips&Media announced licensing of Image Signal Processing (ISP)

Seoul, Korea – February 27th, 2019 -- Chips&Media, a leading video technology provider, reported signing a contract to provide CARPO (Image Signal Processing) and KERBEROS (Lens Distortion Correction) to a leading developer for advanced automotive application SoCs, marking an important milestone as the inception of Chips&Media's Image Processing IPs for the automotive segment.

IPs licensed are the automotive targeted version, where CARPO and KERBEROS are configurable and comprehensive ISP pipeline, and lens distortion correction IPs respectively. In particular, these IPs have integrated Safety/ECC features and the capability to accommodate various sensors’ high-bit inputs (20 bits and 24 bits) into the ISP pipeline.

ISP and LDC are important functionalities in automotive applications to achieve improvements in ADAS such as object detection while providing consistent details and correcting physically distorted images from wide-angle lenses.

“This is a key moment and an important opportunity for us to be part of the team contributing toward high-performance artificial intelligence SoCs for advanced automotive application,” commented Steve Sang-Hyun Kim, the CEO of Chips&Media.

About Chips&Media, Inc.

Chips&Media is the leader in the video hardware IP. Chips&Media’s extensive video IPs, including deep learning-based computer vision, video codec, computational photography, and image signal processing have orchestrated Chips&Media to transform itself as a total Video IP provider. Chips&Media’s IPs had been licensed by over 90 customers, who have acclaimed them for low power usage, high-performance, small-size, reliability, and market references, and these praised IPs range from legacy codecs to computer vision as follows:

Codecs: HEVC, H.264, VP9, AV1, AVS2, and other legacy codecs with resolution up to UHD (4K/8K) at 120 FPS

ISP/Computational Photography: Comprehensive and configurable ISP pipeline, Multi-exposure HDR, 3DNR, Lens Distortion Correction, Multi-instances support

Computer Vision: Deep learning-based object detection IP

To find further information, please visit the company's web site at

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