Brain Magnetic Resonance Imaging Compression Using Daubechies & Biorthogonal Wavelet with the fusion of STW and SPIHT
Subrato Bharati, Prajoy Podder, Md. Raihan Al-Masud · 2018
This paper mainly discusses about digital image (MRI image) compression using different parameters. A database of image contains huge number of images and therefor file size may be in GB or Large MB type. Image data compression is a popular method to reduce the redundancies in data representation in order to decrease image data or file storage requirements and hence communication costs. Reducing the hard drive or system capacity prerequisite is equivalent to accumulating the volume of the storage medium and hence communication bandwidth. This Paper mainly shows the performance of Daubechies & Biorthogonal Wavelet for image level decomposition and compression. SPIHT and STW technique have also been applied in compressing the decomposed brain MRI image and finding the compressed brain MRI image. Input MRI Image can be converted to gray scale image for easy operation. BPP, MSE, PSNR and Compression ratio has also been calculated for not only db wavelet but also bior wavelet in different condition by tuning the parameters. The compression performance has also been represented graphically for different number of decomposition level so that it can be determined which decomposition level gives a user good compression ration with less data loss.