TAILIEUCHUNG - EURASIP Journal on Applied Signal Processing 2003:5, 430–436 c 2003 Hindawi Publishing

EURASIP Journal on Applied Signal Processing 2003:5, 430–436 c 2003 Hindawi Publishing Corporation An Approach to Adaptive Enhancement of Diagnostic X-Ray Images ¨ Hakan Oktem Institute of Signal Processing, Tampere University of Technology, . Box 553, 33101 Tampere, Finland Email: oktem@ Karen Egiazarian Institute of Signal Processing, Tampere University of Technology, . Box 553, 33101 Tampere, Finland Email: karen@ Jarkko Niittylahti Atostek Ltd., Hermiankatu 8D, FIN-33720 Tampere, Finland Email: Juha Lemmetti Atostek Ltd., Hermiankatu 8D, FIN-33720 Tampere, Finland Email: Received 31 January 2002 and in revised form 3 October 2002 Digital radiography is a popular diagnostic imaging method. Denoising and enhancement have an important potential in obtaining. | EURASIP Journal on Applied Signal Processing 2003 5 430-436 2003 Hindawi Publishing Corporation An Approach to Adaptive Enhancement of Diagnostic X-Ray Images Hakan Oktem Institute of Signal Processing Tampere University of Technology . Box 553 33101 Tampere Finland Email oktem@ Karen Egiazarian Institute of Signal Processing Tampere University of Technology . Box 553 33101 Tampere Finland Email karen@ Jarkko Niittylahti Atostek Ltd. Hermiankatu 8D FIN-33720 Tampere Finland Email Juha Lemmetti Atostek Ltd. Hermiankatu 8D FIN-33720 Tampere Finland Email Received 31 January 2002 and in revised form 3 October 2002 Digital radiography is a popular diagnostic imaging method. Denoising and enhancement have an important potential in obtaining as much easily interpretable diagnostic information as possible with reasonable absorbed doses of ionising radiation. Due to the increasing usage of high resolution and high precision images with a limited number of human experts the computational efficiency of the denoising and enhancement becomes important. In this paper a local adaptive image enhancement and simultaneous denoising algorithm for fulfilling the requirements of digital X-ray image enhancement is introduced. The algorithm is based on modification of the wavelet transform coefficients by a pointwise nonlinear transformation and reconstructing the enhanced image from the modified wavelet transform coefficients. The implementation of algorithm in software is simple quick and universal. Keywords and phrases image enhancement X-ray images wavelet shrinkage. 1. INTRODUCTION Typically digital X-ray images are corrupted by additive noise relatively higher with respect to conventional X-ray films. Higher SNR is possible at cost of higher absorbed doses of ionising radiation. Furthermore image enhancement algorithms generally amplify the noise 1 2 3 4 . Therefore higher denoising performance is .

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