As told by its name, fast-openISP is a faster (and bugs-fixed) re-implementation of the openISP project.

Compared to C-style code in the official openISP repo, fast-openISP uses pure matrix implementations based on Numpy, and increases processing speed over 300 times.

Here is the running time in my Ryzen 7 1700 8-core 3.00GHz machine with the 1920x1080 input Bayer array:

^* CEH module is not included in the official openISP pipeline.

Clone this repo and run

python demo.py

The ISP outputs will be saved to ./output directory.

The only required package for pipeline execution is numpy. opencv-python and scikit-image are required only for data IO.

All modules in fast-openISP reproduce processing algorithms in openISP, except for EEH and BCC modules. In addition, a CEH (contrast enhancement) module with CLAHE is added into the fast-openISP pipeline.

The official openISP uses an asymmetric kernel to extract edge map. In fast-openISP, however, we use the subtraction between the original and the gaussian filtered Y-channel as the edge estimation, which reduces the artifact when the enhancement gain is large.

The official openISP enhances the image contrast by pixel-wise enlarging the difference between pixel values and a constant integer (128). In fast-openISP, we use the median value of the whole frame instead of a constant.

Tunable parameters in fast-openISP are differently named from those in openISP, but they are all self-explained, and no doubt you can easily tell the counterparts in two repos. All parameters are managed in a yaml in ./configs, one file per camera.

Bayer Input

CFA Interpolation

Color Correction

Gamma Correction

Non-local Means & Bilateral Filter

Contrast Enhancement

Edge Enhancement

Hue & Saturation Control

Brightness & Contrast Control

Copyright 2021 Qiu Jueqin.

Licensed under MIT.