RIA: Vector Quantization for Image Compression and Processing

图像压缩是减少数据量的过程 需要存储或传输图像。 传统上， 很少考虑图像处理操作， 在压缩步骤之前或之后。 提出要 研究图像压缩和图像处理 可以合并成一个单一的操作，也可以在其中 图像压缩可导致改进或更简单的图像处理 运营 压缩的矢量量化算法 半色调二进制图像将开发和图像将 首先压缩，然后用图像进行半色调处理 然后进行半色调处理和压缩。 矢量量化器可以 同时执行压缩和图像处理任务 例如半色调、逆傅立叶变换和收缩 还将研究如何提高。 这将导致 计算复杂度的降低，如果 压缩步长小于图像处理的步长 操作 最后，将进行检查，以查看图像 压缩将导致更简单或改进的图像处理 图像分割、目标检测和预处理等操作 筛选医学图像中的可疑区域。

Image compression is the process of reducing the amount of data required to store or transmit an image. It has traditionally been done with little regard for image processing operations that may precede or follow the compression step. It is proposed to investigate areas in which image compression and image processing may be combined into a single operation, and also areas in which image compression may lead to improved or simpler image processing operations. Vector quantization algorithms for the compression of halftoned binary images will be developed and images will be compared that are first compressed and then halftoned with images that are halftoned and then compressed. Vector quantizers that can simultaneously perform both compression and image processing tasks such as halftoning, inverse Fourier transforming, and contract enhancement will also be investigated. This will lead to a reduction in computational complexity if the complexity of the compression step is less than that of the image processing operation. Finally, examinations will be done to see if image compression will lead to simpler or improved image processing operations such as image segmentation, target detection, and pre- screening for suspect regions in medical images.