Image Enhancement Image Enhancement UsingUsing

Logarithmic Image Processing Logarithmic Image Processing (LIP)(LIP)

Presented by-Presented by-

Akash MishraAkash Mishra

Roll no. 02Roll no. 02

M.Sc. 3M.Sc. 3rdrd sem sem

IntroductionIntroduction

Histogram method is not always the Histogram method is not always the best best

method for image enhancement, method for image enhancement, especially for color images where especially for color images where equalizing all the three components equalizing all the three components R, G, B may create color distortion.R, G, B may create color distortion.

Logarithmic Image Logarithmic Image ProcessingProcessing

The logarithmic image processing can effectively enhance details The logarithmic image processing can effectively enhance details

in the very dark or very dark or very bright areas of an image, which in the very dark or very dark or very bright areas of an image, which

can be useful for enhancing an underexposed or overexposed image. can be useful for enhancing an underexposed or overexposed image.

This method uses the equation as followsThis method uses the equation as follows

(continue………)(continue………)

Image Enhanced),( jif

n)(n x size ow with windImage Averaged),( jia

))],(log()),([log()),(log()),(log( jiajifjiajif

Image Orignal),( jif

α governs the contrast of the image

β governs the sharpness of the image

(……..)(……..)

Effects of α and β in this equation

•α governs the contrast of the image:•α >1 Brings out bright areas•α <1 Brings out dark areas•α < 0 Negative Transformation

•β governs the sharpness of the image:•β >1 Sharpening•β <1 Blurring

•n x n window also governs the sharpness of the image•Bigger is not always better

Examples of Histogram Equalization isn’t the answerExamples of Histogram Equalization isn’t the answer

Graphical User InterfaceGraphical User Interface

Graphical User InterfaceGraphical User Interface

Enhancing Dark DetailsEnhancing Dark Details

Enhancing Dark DetailsEnhancing Dark Details

Enhancing Dark DetailsEnhancing Dark Details

Enhancing Bright DetailsEnhancing Bright Details

Color EnrichmentColor Enrichment

Our result shows that the algorithm can also create color enrichment to a certain degree. This is something that histogram equalization fails to perform.

The color in the words “U.S AIR FORCE” stands out much more in the enhanced image. Also note that the shadow in the mountain is “deeper” than the original.

Color EnrichmentColor Enrichment

Histogram Equalization creates an illusion that the flight was in bad weather!

Window SizingWindow Sizing

LIP with 3x3 window LIP with 9x9 window

NoiseNoise

F(ij)=B(i,j)+noise

),(

1),(

),(

jiB

noise

jiB

jiF

SummarySummary

ParametersParameters αα controls the contrast controls the contrast enhancement ββ controls the sharpness of the controls the sharpness of the

image.image. Larger Window size => sharper edgesLarger Window size => sharper edges

Superior to Histogram EqualizationSuperior to Histogram Equalization Black and White imagesBlack and White images Color imagesColor images Noisy ImagesNoisy Images

ConclusionConclusion

AdvantagesAdvantages Simultaneous enhancement of contrast Simultaneous enhancement of contrast

and sharpnessand sharpness Fine-tuned control over image Fine-tuned control over image

enhancementenhancement DisadvantageDisadvantage

Parameter values must be carefully Parameter values must be carefully selected and adjusted to obtain desirable selected and adjusted to obtain desirable resultsresults

Questions?Questions?