What Is the Watershed Area?

Watershed, pinyin is fn shu ln, which refers to a mountain or highland that separates two adjacent watersheds; it also compares the main boundary of different things.

[fn shu lng]

Watershed:

The ridge or plateau that divides the two watersheds. Also called the watershed.

compare the main boundaries of different things.

For example, located in Xi'an, Shaanxi

Watershed by

Watersheds that move with time are called unstable watersheds; watersheds that do not move due to river erosion for a long period of time are called stable watersheds. In general, the shape of unstable watersheds is significant and the range is narrow.

Great Divide

Watershed segmentation method is based on topological theory

A watershed is an uphill area where fluid (usually water) is collected at a public water outlet for centralized discharge. It can be part of a larger watershed, or it can contain smaller watersheds called natural subcatchments. The boundary between watersheds is called the watershed boundary. The water outlet or pour point is the point on the surface where the water flows out. It is the lowest point on the watershed boundary.

Watershed

By calculating the flow direction and using the DEM in the Watershed tool, the watershed can be mapped by the DEM.

To determine the confluence area, you must first use the Flow Direction tool to create a grid representing the flow direction.

Then, the location of the catchment area needs to be given. The source location may be a feature such as a dam or river level, and you need to determine the characteristics of the confluence area for it. You can also use traffic

The watershed calculation process is an iterative labeling process. The classic calculation method of watershed was proposed by L. Vincent. In this algorithm, the watershed calculation is divided into two steps, one is the sorting process, and the other is the flooding process. Firstly, the gray level of each pixel is sorted from low to high, and then in the process of submerging from low to high, the first-in-first-out (FIFO) structure is used for the influence domain of each local minimum at the height of h Judge and label.

The watershed transform obtains the watershed image of the input image, and the boundary points between the watersheds are the watersheds. Obviously, the watershed represents the maximum point of the input image. Therefore, in order to obtain the edge information of the image, the gradient image is usually used as the input image, that is,

g (x, y) = grad (f (x, y)) = ([f (x, y) -f (x-1, y)] 2 [f (x, y) -f (x, y- 1)] 2} 0.5

In the formula, f (x, y) represents the original image, and grad {.} Represents the gradient operation.

The watershed algorithm has a good response to faint edges. Noise in the image and slight gray changes on the surface of the object will cause over-segmentation. But at the same time, it should be seen that the watershed algorithm has a good response to weak edges and is guaranteed by closed continuous edges. In addition, the closed catchment basin obtained by the watershed algorithm provides the possibility to analyze the regional characteristics of the image.

In order to eliminate the excessive segmentation generated by the watershed algorithm, two processing methods can usually be adopted. One is to remove the irrelevant edge information by using prior knowledge. The second is to modify the gradient function so that the catchment basin only responds to the target that it wants to detect.

To reduce the over-segmentation generated by the watershed algorithm, the gradient function is usually modified. A simple method is to perform threshold processing on the gradient image to eliminate the over-segmentation caused by small changes in gray scale. which is

g (x, y) = max (grad (f (x, y)), g)

In the formula, g represents a threshold value.

The program can use methods: limit the gradient image with a threshold to eliminate excessive segmentation caused by small changes in gray value, obtain a proper amount of area, and then sort the gray levels of the edge points of these areas from low to high, and then From low to high, the submerged process is realized. The gradient image is calculated by Sobel operator. When thresholding the gradient image, choosing a suitable threshold value has a great impact on the final segmented image. Therefore, the selection of the threshold value is a key factor for the image segmentation effect. Disadvantages: The actual image may contain weak edges, and the difference in the value of the gray level is not particularly obvious. Selecting a too large threshold may eliminate these weak edges.