# Deep Feature Consistent Deep Image Transformations: Downscaling, Decolorization and HDR Tone Mapping

arXiv: https://arxiv.org/abs/1707.09482 · HTML: https://mlsanity.com/paper/1707.09482/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2017.

## Built on by (most cited first, 7 of 7)

- [Unpaired Learning for High Dynamic Range Image Tone Mapping](https://mlsanity.com/paper/2111.00219/) (2021)
- [Approaching the Limit of Image Rescaling via Flow Guidance](https://mlsanity.com/paper/2111.05133/) (2021)
- [Learning a self-supervised tone mapping operator via feature contrast masking loss](https://mlsanity.com/paper/2110.09866/) (2021)
- [Learning Adaptive Lighting via Channel-Aware Guidance](https://mlsanity.com/paper/2412.01493/) (2024)
- [Learning Differential Pyramid Representation for Tone Mapping](https://mlsanity.com/paper/2412.01463/) (2024)
- [Two Decades of Colorization and Decolorization for Images and Videos](https://mlsanity.com/paper/2204.13322/) (2022)
- [Equalization and Brightness Mapping Modes of Color-to-Gray Projection Operators](https://mlsanity.com/paper/2208.09950/) (2022)

## Abstract (arXiv)

Building on crucial insights into the determining factors of the visual integrity of an image and the property of deep convolutional neural network (CNN), we have developed the Deep Feature Consistent Deep Image Transformation (DFC-DIT) framework which unifies challenging one-to-many mapping image processing problems such as image downscaling, decolorization (colour to grayscale conversion) and high dynamic range (HDR) image tone mapping. We train one CNN as a non-linear mapper to transform an input image to an output image following what we term the deep feature consistency principle which is enforced through another pretrained and fixed deep CNN. This is the first work that uses deep learning to solve and unify these three common image processing tasks. We present experimental results to demonstrate the effectiveness of the DFC-DIT technique and its state of the art performances.