KEYWORDS: Quantization, Image compression, Image quality, Computer programming, Image transmission, Image processing, Signal to noise ratio, Telemedicine, Medical imaging, RGB color model
Retinal color images play an important role in supporting medical diagnosis. Digital retinal image usually are
represented in such a large data volume that takes a considerable amount of time to be accessed and displayed from
remote site. This paper aims to conduct a color retinal image coding using Entropy-Constrained Vector Quantization
(ECVQ). In this paper, we use two objective parameters: Mean Square Error (MSE) and Peak Signal to Noise Ratio
(PSNR). Coded image which has the best quality of subjective and objective is the image coded with the value of λ = 0.1
and rate = 4.5 bpp.
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