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quantization process
Translation of "quantization process" in Chinese
量化过程
a quantization unit configured to generate edge image data by performing a quantization process on the edge intensity image data,
Because this quantization process is applied individually in each block, neighboring blocks quantize coefficients differently.
因為這個量化的處理過程是被單獨的應用在每一個區塊，所以相鄰區塊係數的量化皆不同。
Further, the image processing unit may have an edge extraction unit configured to generate edge intensity image data by performing an edge extraction process on the captured image data, a quantization unit configured to generate edge image data by performing a quantization process on the edge intensity image data, an edge labeling unit configured to regard edge pixel regions having connectivity with the edge image data as a same region, to perform a process of giving a same label number to edge pixels of the same region, and to generate labeled image data, a first rectangle objectification unit configured to perform a process of giving a circumscribed rectangle to the edge pixel regions to which the same label number is given based on the labeled image data, and to generate a rectangular object, and a first fine object removal unit configured to perform a process on the edge image data to remove an edge pixel region having a small number of connected pixels and an edge pixel region in a rectangular object having short vertical and horizontal widths as noise based on the labeled image data and the rectangular object, and to generate output edge image data.
进一步，图像处理单元可具有：边缘提取单元，用于通过对捕捉图像数据进行边缘提取过程而生成边缘强度图像数据；量化单元，用于通过对边缘强度图像数据进行量化过程而生成边缘图像数据；边缘标记单元，用于将与边缘图像数据具有连通性的边缘像素区域视为同一区域，进行对同一区域的边缘像素提供相同标记号码的过程，并生成标记图像数据；第一矩形对象化单元，用于基于标记图像数据进行对具有相同标记号码的边缘像素区域提供外切矩形的过程，并生成矩形对象；第一对象精细清除单元，用于基于标记图像数据和矩形对象对边缘图像数据进行该过程：将连接像素数量少的边缘像素区域以及矩形对象内垂直和水平宽度短的边缘像素区域作为噪声而清除，并生成输出边缘图像数据。
Other results
Several algorithms of process data compression are introduced in detail, such as box car, backward slope, SDT, PLOT and vector quantization.
This part of the process is often called "inverse quantization" or "dequantization", although quantization is an inherently non-invertible process.
The edge labeling unit 203 regards edge pixel regions having connectivity on the edge image data generated by the quantization unit 202 as the same region, and performs a process of giving the same label number to edge pixels in the same region and thereby generates labeled image data.
边缘标记单元203将在量化单元202生成的边缘图像数据上具有连通性的边缘像素区域视为同一区域，进行对同一区域的边缘像素提供相同标记号码的过程，从而生成标记图像数据。
The fine object removal unit 205 performs a noise removal process on the edge image data generated by the quantization unit 202 and the labeled image data generated by the edge labeling unit 203, and thereby generates output edge image data and output labeled image data.
对象精细清除单元205对量化单元202生成的边缘图像数据和边缘标记单元203生成的标记图像数据进行噪声消除过程，从而生成输出边缘图像数据和输出标记图像数据。
The entire process of transform and quantization can be carried out using 16-bit integer and only a single multiply per coefficient without any loss of accuracy and inverse transform mismatch.
整数变换是一种只有加法和移位的运算，量化可以通过查表和乘法操作就可以完成，避免了反变换的时候失配问题，没有精度损失；
FIG. 2 is a functional block diagram of an encoding process 200 including static content detection in accordance with various embodiments of the present disclosure. In this diagram, static content detection is primarily performed by skip decision functionality 202 operating in conjunction with hash code storage 204. Briefly, in various embodiments a skip decision may be reached by comparing hash codes/check values (or the like) of (1) a current input macro-block or slice and (2) a co-located previous input macro-block or slice in order to identify a static portion(s) of video input. In one alternate embodiment, a skip decision may involve comparing hash codes of (1) a reconstructed version of an input macro-block or slice and (2) a reconstructed version of a co-located previous macro-block or slice. In such an embodiment, the reconstructed version of the input macro-block or slice may be generated by prediction, transform and quantization functionality 210. Details of an embodiment of skip decision functionality 202 are described below in conjunction with FIG. 3.
图2为根据本发明各个实施例的包括静态内容检测的编码过程200的功能框图。在该图中，静态内容检测主要由与散列码存储器204结合运行的跳跃判定功能202进行。简短地说，在各个实施例中，可通过比较（1）当前输入宏块或片和（2）先前同位输入宏块或片，以识别视频输入的静态部分而实现跳跃判定。在一个替代实施例中，跳跃判定可涉及（1）输入宏块或片的重构版和（2）先前同位宏块或片的重构版的散列码的比较。在这种实施例中，输入宏块或片的重构版可由预测、转换和量化功能210生成。下文结合图3对跳跃判定功能202的一个实施例进行了详细说明。
Synonyms and analogies of "quantization process" in English
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