Model-Based Color Image Sequence Quantization y

Sequential scalar quantization of color images

An efficient algorithm for color image quantization is proposed based on a new vector quantization technique that we call sequential scalar quantization. The scalar components of the 3-D color vector are individually quantized in a predetermined sequence. With this technique, the color palette is designed very efficiently, while pixel mapping is performed with no computation. To obtain an optim...

کاهش رنگ تصاویر با شبکه‌های عصبی خودسامانده چندمرحله‌ای و ویژگی‌های افزونه

Reducing the number of colors in an image while preserving its quality, is of importance in many applications such as image analysis and compression. It also decreases memory and transmission bandwidth requirements. Moreover, classification of image colors is applicable in image segmentation and object detection and separation, as well as producing pseudo-color images. In this paper, the Kohene...

Multiobjective Image Color Quantization Algorithm Based on Self-Adaptive Hybrid Differential Evolution

In recent years, some researchers considered image color quantization as a single-objective problem and applied heuristic algorithms to solve it. This paper establishes a multiobjective image color quantization model with intracluster distance and intercluster separation as its objectives. Inspired by a multipopulation idea, a multiobjective image color quantization algorithm based on self-adap...

Bayesian Inferen e for Color Image Quantization via Model-Based Clustering Trees

Model-Based Halftoning for Color Image Segmentation

Grouping algorithms based on histograms over measured image features have very successfully been applied to textured image segmentation [2, 11, 6]. However, the competing goals of statistical estimation significance demanding few quantization levels versus the necessary richness in representation often prevent a successful application for the color cue, since quantization may result in contouri...