Punys Vytenis, Maknickas Ramunas
Department of Multimedia Engineering, Kaunas University of Technology, Lithuania.
Stud Health Technol Inform. 2011;169:470-4.
Big virtual microscopy images (80K x 60K pixels and larger) are usually stored using the JPEG2000 image compression scheme. Diagnostic quantification, based on image analysis, might be faster if performed on compressed data (approx. 20 times less the original amount), representing the coefficients of the wavelet transform. The analysis of possible edge detection without reverse wavelet transform is presented in the paper. Two edge detection methods, suitable for JPEG2000 bi-orthogonal wavelets, are proposed. The methods are adjusted according calculated parameters of sigmoid edge model. The results of model analysis indicate more suitable method for given bi-orthogonal wavelet.
大型虚拟显微镜图像(80K×60K像素及更大)通常使用JPEG2000图像压缩方案进行存储。基于图像分析的诊断量化,如果对压缩数据(约为原始数据量的二十分之一)进行,可能会更快,压缩数据代表小波变换的系数。本文介绍了在不进行逆小波变换的情况下进行可能的边缘检测分析。提出了两种适用于JPEG2000双正交小波的边缘检测方法。这些方法根据sigmoid边缘模型的计算参数进行调整。模型分析结果表明了给定双正交小波更合适的方法。