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Adaptive bilateral filter for sharpness enhancement and noise removal

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Presented By:
Zhang B, Allebach JP.
Texas Instruments, Inc, TX 75243, USA.

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Abstract
In this paper, we present the adaptive bilateral filter (ABF) for sharpness enhancement and noise removal. The ABF sharpens an image by increasing the slope of the edges without producing overshoot or undershoot. It is an approach to sharpness enhancement that is fundamentally different from the unsharp mask (USM). This new approach to slope restoration also differs significantly from previous slope restoration algorithms in that the ABF does not involve detection of edges or their orientation, or extraction of edge profiles. In the ABF, the edge slope is enhanced by transforming the histogram via a range filter with adaptive offset and width. The ABF is able to smooth the noise, while enhancing edges and textures in the image. The parameters of the ABF are optimized with a training procedure. ABF restored images are significantly sharper than those restored by the bilateral filter. Compared with an USM based sharpening method-the optimal unsharp mask (OUM), ABF restored edges are as sharp as those rendered by the OUM, but without the halo artifacts that appear in the OUM restored image. In terms of noise removal, ABF also outperforms the bilateral filter and the OUM. We demonstrate that ABF works well for both natural images and text images

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http://ieeexplore.ieeeiel5/83/4484077/04476197.pdf
http://www.einfodailypiTunez/bilateral.pdf

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Presented By:
BATCH NO:07
M.RAVALI(06K61A0445)
M.N.VENKATESH BABU.S(06K61A0426)
M.SANDEEP(07K65A0404)
CH.TEJ KUMAR(06K61A0456)
K.RATNA DEEPIKA(06K61A0444)

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ABSTRACT
IN THIS PROJECT, WE PRESENT THE ADAPTIVE BILATERAL FILTER (ABF) FOR SHARPNESS ENHANCEMENT AND NOISE REMOVAL
ËœABFâ„¢ SHARPENS AN IMAGE BY INCREASING THE SLOPE OF THE EDGES WITHOUT PRODUCING OVERSHOOT OR UNDERSHOOT
IT IS DIFFERENT FROM THE UNSHARP MASK (USM)
THE ABF DOES NOT INVOLVE DETECTION OF EDGES OR THEIR ORIENTATION, OR EXTRACTION OF EDGE PROFILES



SCOPE
THE SCOPE OF THIS PROJECT IS TO DEAL WITH IMAGES THAT ARE APPROPRIATE FOR DIGITAL PHOTOGRAPHY.
WE DO NOT CONSIDER IMAGES THAT ARE SEVERELY DEGRADED.



MODULES
DEGRADATION OF IMAGE
BILATERAL FILTERING
ADAPTIVE BILATERAL FILTERING
REGION OF INTEREST




IMAGE ENHANCEMENT:
“ A PROCESS WHICH AIMS TO IMPROVE BAD IMAGES SO THEY WILL LOOK BETTER.
NO QUANTITATIVE MEASURES
SUBJECTIVE


IMAGE RESTORATION:
“ A PROCESS WHICH AIMS TO INVERT KNOWN DEGRADATION OPERATIONS APPLIED TO IMAGES.
MATHEMATICAL, MODEL DEPENDENT QUANTITATIVE MEASURES
OBJECTIVE


ALGORITHM FOR BILATERAL FILTER
TAKE IMAGE AS INPUT AND ALSO RANGE FILTER AND DOMAIN FILTER VALUES
CALCULATE GAUSSIAN WEIGHTS
CALCULATE A SMALLER WINDOW
CALCULATE NORMALIZATION FACTOR FOR THE WINDOW
CALCULATE THE IMPULSE RESPONSE OF THE WINDOW
REPEAT THE PROCESS FROM THIRD STEP TILL THE SIZE OF WHOLE IMAGE
SEND THE IMAGE AS OUTPUT
OUTPUT OF BILATERAL FILTER
ADVANTAGES & LIMITATIONS


ADVANTAGES
FAST
SIMPLE
INTUITIVE PARAMETER SELECTION
EDGES PRESERVING


LIMITATIONS
OVER SMOOTH
CANâ„¢T ITERATE MANY TIMES


ADAPTIVE BILATERAL FILTER
THE ABF RETAINS THE GENERAL FORM OF A BILATERAL FILTER, BUT
ABF CONTAINS TWO IMPORTANT MODIFICATIONS. FIRST, AN OFFSET IS INTRODUCED TO THE RANGE FILTER IN THE ABF.
SECOND, BOTH AND THE WIDTH OF THE RANGE FILTER IN THE ABF ARE LOCALLY ADAPTIVE