An adaptive and deterministic method for initializing the Lloyd-Max algorithm

Gray-level quantization (reduction) is an important operation in image processing and analysis. The Lloyd- Max algorithm (LMA) is a classic scalar quantization algorithm that can be used for gray-level reduction with minimal mean squared distortion. However, the algorithm is known to be very sensitive to the choice of initial centers. In this paper, we introduce an adaptive and deterministic algorithm to initialize the LMA for gray-level quantization. Experiments on a diverse set of publicly available test images demonstrate that the presented method outperforms the commonly used uniform initialization method.