PAAVAI COLLEGE OF ENGINEERING

COMPARISON OF TONE-MAPPING ALGORITHM BASED ON

STRUCTURAL FIDELITY AND STATISTICAL NATURALNESS

PRESENTED BY:

JUVVALAPALEM SUMADEEP

R.G.GOWTHAM

R.KARTHICK

GUIDED BY:

R.KARTHICK..,ASST PROF

OBJECTIVES

• The objective of this project is to allow the

HDR images on LDR visual displays. Here we

propose an objective quality assessment

algorithm for tone- mapped images by

combining: 1) a multi scale signal fidelity

measure on the basis of a modified structural

similarity index and 2) a naturalness measure

on the basis of intensity statistics of natural

images.

ABSTRACT

Tone-mapping operators[TMOs] that converting high

dynamic range[HDR] to low dynamic range[LDR]

images practically useful tools for the visualization of

HDR images on standard LDR displays by comparing

statistical naturalness and structural fidelity.

LITERATURE SURVEY

RECOVER REAL WORLD SCENE

OBJECTIVES:

• The objective of this project is a new method of high quality image in paintingfor recovering original scene of degraded image using reference images ofdifferent exposures.

TOOLS:

• Inter-pixel relationship function , Dual patching.

DEMERITS:

• Useful data can be lost due to camera shake , especially when capturing by ahand device , which generates noticeable artefact in the synthesized image.

FAST MOVEMENT DETECTION FOR HDR

IMAGING

OBJECTIVES:

The objective of this project is improving a quality and speed of final HDR images .

TOOLS:

Sub sampling method , new adaptive threshold , new patching .

DEMERITS:

If a pixel is detected as a background one , its neighboring pixels are skipped .

COMPARISION

EXISTING SYSTEM

HDR images doesn’t clearly visible on standard LDR displays.

Losses will occurred while allowing HDR image on LDR displays.

It is expensive and time consuming.

Manual parameter tuning.

Image quality is poor

PROPOSED

SYSTEM

HDR images are allowed to visible on standard LDR displays.

Losses will removed using adaptive fusion tone-mapping technique

Cheaper

Automatic parameter tuning.

Image quality is high

PROPOSED BLOCK DIAGRAM

LDR image created by TMO or

photoshop

LDR image created by TMO or

photoshop

Decomposition Laplacian

pyramid transform

Decomposition Laplacian

pyramid transform

Scale1 Fused Scale1

Scale2 Fused Scale2

Scale3 Fused Scale3

Scale4 Fused Scale4

Reconstruction

ALGORITHM

Take an HDR image

Convert HDR image in to LDR image using TMO’s orPhotoshop

Compare the quantity, local intensity and naturalness oftwo images

Take an high quality image from the compared images

Choose the high parameter image that was above thethreshold

If the image parameter is below the threshold then it willrepeated the same process

The HDR image will displayed in LDR displays

FLOW CHART

LDR image created by TMO or

photoshop

Structural

fidelity

Statistical

naturalness

Quality assessment

Parameters are above

threshold

Output image

Parameter tuning

MODULE PHASE 1

QUALITY ASSESSMENT METHOD OF TONE-MAPPING OPERATORS:

Tone-mapping operators that convert high dynamic range image to low dynamic range and allow to make visible on LDR displays.

quality assessment method that defines to achieve a good comparison between structural fidelity and structural naturalness.

The algorithms using in this are:

Structural fidelity

statistical naturalness

STRUCTURAL FIDELITY

It compare luminance, contrast & structure of LDR & HDR.

It extract the information about image structure.

It based on two intuitive

signal strength is significant

signal strength is insignificant

Estimated value applied in sliding window technique for

obtain structure of image.

STATISTICAL NATURALNESS

Important for image processing application &

biological vision

A high quality tone mapped LDR image should

not only faithfully preserve the structural

fidelity of the HDR image but also look natural

It discuss about the naturalness of the image

quantity.

MODULE PHASE 2

PARAMETER TUNING

The parameter tuning automatically adjust the

parameter values of the image which can be done

by using TMQI.

It consists two coefficient values SRCC and

KRCC.

These values compare with threshold value

and dynamic range of the image automatically

Adaptive fusion

Adaptive fusion technique which is used for combine many TMO images and objective quality measure.

It can be done by using Discrete wavelet transform.Wavelets work for decomposing signals (such asimages) into hierarchy of increasing resolutions: as weconsider more layers, we get more and more detailedlook at the image.

At first laplacian pyramid transform decompose image into different scales and find the coefficient value.

Then the fusion technique applied for an multiple co-efficient, the image to be reconstruct.

REFERENCE’S

• Eric c. Larson, Damon M. Chandler, “Most apparentdistortion: full-reference image quality assessment and therole of strategy”, journal of electronic imaging 19(1),011006, Mar 2010.

• Fredo Durand, Julie Dorsey,” Fast Bilateral imaging forthe recovery of High Dynamic Range imaging”,Massachusetts Institute of Technology,2002.

• Hojatollah Yeganeh, “Objective Quality Assessment ofTone-Mapped Images”, student Member, IEEE, and ZhouWang, Member, IEEE Transactions on imageprocessing,VOL.22, NO.2, Feb 2013.

• Z. J. Zhu, Z.G. Li, S. Rahardja, and P. Franti, “Recoverreal world scene: high quality image in painting usingmulti-exposed references”, Electronics Letters, PP.1310-1312, VOL. 45, Issue 25, Dec 2009.