Abstract

The tone-mapping algorithm compresses the high dynamic range (HDR) information into the standard dynamic range for regular devices. An ideal tone-mapping algorithm reproduces the HDR image without losing any vital information. The usual tone-mapping algorithms mostly deal with detail layer enhancement and gradient-domain manipulation with the help of a smoothing operator. However, these approaches often have to face challenges with over enhancement, halo effects, and over-saturation effects. To address these challenges, we propose a two-step solution to perform a tone-mapping operation using contrast enhancement. Our method improves the performance of the camera response model by utilizing the improved adaptive parameter selection and weight matrix extraction. Experiments show that our method performs reasonably well for overexposed and underexposed HDR images without producing any ringing or halo effects.

Highlights

  • Casual photographic devices can represent a fraction of the high dynamic range (HDR) images due to their limited irradiance range

  • That is why HDR images displayed by regular devices often look overexposed or underexposed

  • We need a proper tone-mapping algorithm to compress the HDR data into the standard dynamic range (SDR), which is compatible with regular devices

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Summary

Introduction

Casual photographic devices can represent a fraction of the HDR images due to their limited irradiance range. A typical tone-mapping algorithm tries to transform the HDR image into an SDR image without losing any vital spatial information. Even though a significant amount of variance is present in previous tone-mapping algorithms, many studies propose using a base-and-detail layer decomposition to transform HDR into SDR. In this method, the base layer and the detail layer are extracted with the help of a standard edge-aware smoothing algorithm

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