&lt;title&gt;Approximate Karhunen-Loeve transform for image processing&lt;/title&gt;

Kurashov, Vitalij N.; Musatenko, Yurij S.

doi:10.1117/12.234731

Cited by 5 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nu +ve and Nu all denote the binary images representing the segmented nuclei in D DAB and D Htx images, respectively. Because of limited contrast of the D Htx image, we perform contrast‐stretching using a nonlinear intensity transformation derived from Karhunen–Loùve Transform on the D Htx image (Eq. ).…”

Section: Methodsmentioning

confidence: 99%

Computer‐aided molecular pathology interpretation in exploring prospective markers for oral submucous fibrosis progression

et al. 2015

View full text Add to dashboard Cite

show abstract

Section: Methodsmentioning

confidence: 99%

Computer‐aided molecular pathology interpretation in exploring prospective markers for oral submucous fibrosis progression

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Such ciiterion may be an entropy or any other cost function. Let H({F}) be, the chosen criterion thnction Then if KL transform (1 will give the global maximum to H, we will say that the best approximation to the KL transform from a libraiy 'is the transform U which satisfy the equation: H(UF)=max, Ue (5) It was shown by Wickerhauser4' 12 that efficient search algorithm can be utilized to minimize entropy over all bases that fall from the tree. It finished the wavelet approximate KL basis construction.…”

Section: Fast Wavelet Algorithm For Approximate Kl Transformmentioning

confidence: 99%

<title>Pattern recognition with fast feature extraction</title>

1998

Self Cite

View full text Add to dashboard Cite

The comparison ofrecently suggested algorithms of fast approximate Karhunen-Loeve(KL) transform when applied to pattern recognition problem is presented. It is known that adequate signs selection is stiff the problem. In the paper we consider several algorithms that can perform fast and quafltative signs selection. Among them are wavelet based algorithm of approximate XL transform, 2D algorithm ofKL transform. algorithm with projection into proper orthogoxialized basis, and real tinie algorithm ofKL transform. To compare quality ofthe algorithms they are apphed to human facts tecognition prob1m. Th evem'y of the all abovementioned algorithms is demonstrated.

show abstract

“…Usually q 4-10. Then we construct POB for every Y. g = {s R' k = O,Ni,} (s ,s) = 8kj (9) Note that {s) mapped into R" constitute complete orthogonal basis for . Then each J" can be represented as v,: = , or V = .C .…”

Section: Algorithm Of True Kl Basis Construction With Low Memory Requmentioning

confidence: 99%

<title>Optimal color coding for compression of true color images</title>

Musatenko

Kurashov

1998

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

In the paper we present the method that improves iossy compression of the true color or other multispectral images. The essence of the method is to project initial color planes into Karhunen-Loeve (KL) basis that gives completely decorrelated representation for the image and to compress basis functions instead ofthe planes. To do that the new fast algorithm of true KL basis construction with low memoiy consumption is suggested and our recently proposed scheme for finding optimal losses ofKL functions while compression is used. Compare to standard JPEG compression ofthe CMYK images the method provides the PSNR gain from 0.2 to 2 dB for the convenient compression ratios. Experimental results are obtained for high resolution CMYK images. It is demonstrated that presented scheme could work on common hardware.

show abstract

<title>Approximate Karhunen-Loeve transform for image processing</title>

Cited by 5 publications

References 0 publications

Computer‐aided molecular pathology interpretation in exploring prospective markers for oral submucous fibrosis progression

Computer‐aided molecular pathology interpretation in exploring prospective markers for oral submucous fibrosis progression

<title>Pattern recognition with fast feature extraction</title>

<title>Optimal color coding for compression of true color images</title>

Contact Info

Product

Resources

About