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Adaptive noise reduction of scintigrams with a wavelet transform
Koichi Ogawa1, Masahiko Sakata, Yu Li
1Department of Applied Informatics, Faculty of Science and Engineering, Hosei University, Tokyo 184-8584, Japan.
Abstract:
The aim of this study was to eliminate the effect of Poisson noise in scintigrams with a wavelet thresholding method. We developed a new noise reduction method with a wavelet transform. The proposed method was a combination of the translation-invariant denoising method and our newly introduced denoising filter which was applicable for Poisson noise. To evaluate the validity of our proposed method, phantom images and scintigrams were used. The results with the phantom images showed that our method was better than conventional methods in terms of the peak signal-to-noise ratio by 3 dB. Quality of the scintigrams processed with our method was better than that with the conventional methods in terms of reducing Poisson noise while preserving edge components. The results demonstrated that the proposed method was effective for the reduction of Poisson noise in scintigrams.
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