首页> 外文会议> >New classified vector quantization with quadtree segmentation for image coding
【24h】

New classified vector quantization with quadtree segmentation for image coding

机译:具有四叉树分割的新分类矢量量化用于图像编码

获取原文

摘要

A new variable block-size, classified vector quantization (VQ) scheme for image compression is presented. A quadtree segmentation is employed to generate blocks of variable size according to their activity. Inactive areas are coded by a predictive VQ of low encoding rate, while active areas are coded by an edge-classified VQ to avoid edge degradation. Both the segmentation and the edge classification are determined by a simple universal contrast identifier. It is shown that the performance of this scheme is competitive with other classified VQ-based approaches, while the coding complexity is relatively low.
机译:提出了一种新的可变块大小,分类矢量量化(VQ)图像压缩方案。使用四叉树分段来根据其活动生成大小可变的块。非活动区域由低编码率的预测VQ编码,而活动区域由边缘分类的VQ编码以避免边缘降级。分割和边缘分类均由简单的通用对比度标识符确定。结果表明,该方案的性能与其他基于VQ的分类方法相比具有竞争优势,而编码复杂度却相对较低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号