Git Product home page Git Product logo

high-dynamic-range-image's Introduction

high-dynamic-range-image

Creating HDR image from image stack with multiple exposures

Introduction

The goal of this project is to recover high dynamic range radiance maps from photographs to crease an image that captures details from the entire dynaimic range. This project has two parts, radiane map construction and tone mapping. For the first part, we implement algorithm from Debevec, Malik to recover high dynamic range radiance map. Then we apply tone mapping and intensity adjustmemt to to convert the radiance map into displayable image.

Algorithm Overview

High Dynamic Range Radiance Map Construction

  1. Film Response Curve Recovery

Film response curve is a function maps from observed pixel values on an image to the log of exposure values: g(Zij) = ln(Ei) + ln(tj). To recover function g, we implement equation from Debevec

g is the unknown response function

w is a linear weighting function. g will be less smooth and will fit the data more poorly near extremes (Z=0 or Z=255). Debevec introduces a weighting function to enphasize the smoothness fitting terms toward the middle of the curve.

t is the exposure time

E is the unknown radiance

Z: is the observed pixel value

i is the pixel location index.

j is the exposure index

P is the total number of exposures.

This response curve can be used to determine radiance values in any images acquired by the imaging processing associated with g, not just the images used to recover the response curve.

  1. High Dynamic Range Radiance Map Construction

Once the response curve g is recovered, we can construct a radiance map based on equation from Debevec

In order to reducing noise in the recovered radiance value, we use all the available exposrues for a particular pixel to computer its radiance based on equation 6 in Debevec.

Tone Mapping

Global tone mapping: In this project, we use gamma correction as global tone mapping. The output image is proportional to the input raised to the power of the inverse of gamma and has pixel value range from 0 to 255.

Color Adjustment

In order to construct HDR image to be as closer to input image as possible, we adjust the output image average intensity for each channel (B, G, R) to be the same as template image. In general, we use middle image from image stack as template, which is usually most representative of the ground truth.

Result 1

Original image


Exposure 1/160 sec

Exposure 1/125 sec

Exposure 1/80 sec

Exposure 1/60 sec

Exposure 1/40 sec

Exposure 1/15 sec

HDR image

Result 2

Original image


Exposure 1/400 sec

Exposure 1/250 sec

Exposure 1/100 sec

Exposure 1/40 sec

Exposure 1/25 sec

Exposure 1/8 sec

Exposure 1/3 sec

HDR image

high-dynamic-range-image's People

Contributors

vivianhylee avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.