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Image representation using block pattern models and its image processing applications

机译:使用块模式模型的图像表示及其图像处理应用

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摘要

An image representation scheme using a set of block pattern models (BPMs) consisting of three categories (constant, oriented, and irregular) is introduced. Algorithms for model classification, model parameter estimation, and image reconstruction from model parameters are presented, and these provide the necessary vehicles for applying the proposed representation scheme to various image processing tasks. The applications of the proposed models in image coding, image zooming, and image smoothing are described. Satisfactory coded images have been obtained at bit rates between 0.5 approximately 0.6 b.p.p. (bits per pixel) with a high-rate realization and between 0.3 approximately 0.5 b.p.p. with a low-rate realization. The high-rate realization has a simple structure suitable for real-time implementation. The methods for image zooming and smoothing are similar, where both adapt the processing for each pixel according to the model of its neighborhood. By using directional filters in oriented regions, edges and lines are rendered sharper in a smoother manner than with conventional linear filtering approaches, which leads to significant improvement in perceived image quality.
机译:介绍了使用一组由三个类别(恒定,定向和不规则)组成的块模式模型(BPM)构成的图像表示方案。提出了用于模型分类,模型参数估计和根据模型参数重建图像的算法,这些算法为将拟议的表示方案应用于各种图像处理任务提供了必要的手段。描述了所提出的模型在图像编码,图像缩放和图像平滑中的应用。已经以0.5〜0.6b.p.p的比特率获得了令人满意的编码图像。 (每个像素的位数)具有较高的实现率,且介于0.3到0.5 b.p.p之间。实现率低。高速实现具有适合实时实现的简单结构。图像缩放和平滑的方法相似,两种方法均根据每个像素的邻域模型调整处理。与传统的线性滤波方法相比,通过在定向区域中使用定向滤波器,可以以更平滑的方式使边缘和线条更清晰,从而显着改善了感知的图像质量。

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