灰度图像 Grayscale Binary_image

https://en.wikipedia.org/wiki/Grayscale

https://zh.wikipedia.org/wiki/灰度图像

In photography and computing, a grayscale or greyscale digital image is an image in which the value of each pixel is a single sample, that is, it carries only intensity information. Images of this sort, also known as black-and-white, are composed exclusively of shades of gray, varying from black at the weakest intensity to white at the strongest.[1]

Grayscale images are distinct from one-bit bi-tonal black-and-white images, which in the context of computer imaging are images with only two colors, black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between.

灰度图像与黑白图像不同,在计算机图像领域中黑白图像只有黑白两种颜色,灰度图像在黑色与白色之间还有许多级的颜色深度。

https://zh.wikipedia.org/wiki/二值图像

https://en.wikipedia.org/wiki/Binary_image

A binary image is a digital image that has only two possible values for each pixel. Typically, the two colors used for a binary image are black and white, though any two colors can be used. The color used for the object(s) in the image is the foreground color while the rest of the image is the background color.[1] In the document-scanning industry, this is often referred to as "bi-tonal".

Binary images are also called bi-level or two-level. This means that each pixel is stored as a single bit—i.e., a 0 or 1.

A binary image can be stored in memory as a bitmap, a packed array of bits. A 640×480 image requires 37.5 KiB of storage. Because of the small size of the image files, fax machine and document management solutions usually use this format. Most binary images also compress well with simple run-length compression schemes.

Binary images can be interpreted as subsets of the two-dimensional integer lattice Z2; the field of morphological image processing was largely inspired by this view.

二值图像是每个像素只有两个可能值的数字图像。人们经常用黑白B&W单色图像表示二值图像,但是也可以用来表示每个像素只有一个采样值的任何图像,例如灰度图像等。

二值图像经常出现在数字图像处理中作为图像掩码或者在图像分割二值化dithering的结果中出现。一些输入输出设备,如激光打印机传真机、单色计算机显示器等都可以处理二值图像。

二值图像经常使用位图格式存储。

二值图像可以解释为二维整数格 Z2图像变形处理领域很大程度上就是受到这个观点启发。

原文地址:https://www.cnblogs.com/rsapaper/p/5999931.html