Progress with an “all-wavelet” approach to image enhancement and de-noising of direct digital thorax radiographic images

Bolet, J.-P.; Cowen, Arnold R.; Launders, Jason; Davies, J. L.; Parkin, G.J.S.; Bury, R.F.

doi:10.1049/cp:19970892

Cited by 4 publications

(2 citation statements)

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“…A related technique is enhancement of high frequency details (sharpening). A variety of preprocessing techniques for chest radiographs based on local equalization, sharpening and combinations and modifications of these techniques have been proposed [98,41,176,180,218,109,21,230], sometimes not only through software but also by using hardware [23,78]. Nowadays almost all vendors sell digital chest units with a larger dynamic range than conventional units and most vendors automatically preprocess the images with proprietary algorithms.…”

Section: General Processing Enhancementmentioning

confidence: 99%

Computer aided diagnosis in chest radiography

Mouton¹,

Douglas

2003

Academic Radiology

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Section: General Processing Enhancementmentioning

confidence: 99%

Computer aided diagnosis in chest radiography

Mouton¹,

Douglas

2003

Academic Radiology

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“…A nonlinear multi-scale contrast enhancement algorithm for chest radiographs based on local contrast information was proposed in [3]. Wavelet transformation was used for contrast enhancement of mammographic images in [4] and chest radiographs in [5]. Comparison of Laplacian and wavelet pyramids with the purpose of contrast enhancement for radiography images was performed in [6].…”

Section: Introductionmentioning

confidence: 99%

Thresholding approach to radiography image processing acceleration

Ostojić¹,

Starcevic²,

Petrović³

2017

Telfor

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Abstract-An approach for detecting low-value Laplacian pyramid coefficients which can be used to accelerate radiography image processing is presented. The acceleration is achieved through modifying Laplacian pyramid construction algorithm. Detection of low-value coefficients in lower pyramid layers is based on corresponding low-value higher layer coefficients which are lower than the threshold. Detected coefficients are then omitted in pyramid calculation and by the radiography image enhancement algorithm. Clinical radiography images are used to evaluate the proposed approach. Structural similarity index (SSIM) is employed to measure similarity between images processed with and without proposed acceleration. Threshold value analysis shows that high image quality with a mean SSIM of 0.995 can be achieved with mean processing time reduction of 4.62 %.

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