PENERAPAN ALGORITMA K-MEANS PADA KOMPRESI ADAPTIF CITRA MEDIS MRI - I Wayan Angga Wijaya; Afriliana Kusumadewi (Jurnal Informatika, 2016)
MRI medical image processing require large amounts of memory. Due to limited bandwidth and storage capacity, the image must be compressed prior to transmission and stored. This paper has the objective to implement the algorithm k means the MRI medical image compression. Implementation begins with the Pre post. At this stage, L-dimensional vector of the image will be made. L is the block - a measure used for clustering technique, but is set back in the form of an array. Then the process of clustering. At this stage, every pixel of the image is represented by the centroid of the cluster. And the last stage is the Main Compression, the pixels that do not contain important information will be removed. The study compared the quality of the original image and compressed image. Based on manual observation, there is no significant difference in quality between the original image and the compressed one.