KR20080064762A - Ocean vegetation image - Google Patents

Abstract

An ocean vegetation image method is provided to obtain an OVI(Ocean Vegetation Index) from a satellite or an air photo image and to visualize the index, using only red, green, and blue band materials for enabling quantitative calculation of the distribution of the plankton from the OVI. An ocean vegetation image method comprises the steps of; calculating red, green, and blue color indexes of a color image(30); visualizing an ocean vegetation index from the green color index, using a satellite or an air photo image(40,70); overlapping the red, the green, and the blue color indexes with each other to visualize the ocean features(50,80); and visualizing the red tide distribution from the red color index(60,90).

Description

Ocean Vegetation Image Method {Ocean Vegetation Image}

1 is a flow chart of marine vegetation image production

2 is a diagram of the main formula used in the present invention

<Description of the symbols for the main parts of the drawings>

2, 2, R, G, and B are red, green, and blue brightness, respectively.

I _R , I _G , and I _B of FIG. 2 are red, green, and blue color indexes, respectively (color index 0

I _C , I _M and I _Y in FIG. 2 are cyan, magenta and yellow color indexes, respectively.

Lillesand, TM and RW Kiefer, 2000, Remote Sensing and Image Interpretation, 4th Ed., John Wiley & Sons, Inc., 724 pp.

The present invention relates to a method of vividly visualizing the image of the ocean from the surface color image data observed by satellites or aircraft and to view the distribution of plankton in the ocean.

The reflection of sunlight from the sea surface is much smaller than on land, and the image of the sea surface is darker than on land. The degree of reflected light from sea level is similar anywhere in the ocean, so characteristics such as the distribution of plankton in the ocean rarely appear in color images. Since seawater absorbs almost 100% of sunlight near infrared rays, visible light bands are mainly used for ocean color detection, and radiometric resolution is used to distinguish minute differences in spatial seawater characteristics. High data) is used. SeaWiFS or MODIS satellites that detect sea color detect high radiation resolutions of 2048 or higher for various wavelengths in the visible range.

Seafaring Exploration Satellite Data The representative extraction of several visible light bands is the distribution of marine chlorophyll (chlorophyll). It is almost impossible to characterize the vegetation distribution of the oceans from LANDSAT or SPOT satellite data, which are land survey satellites containing only R (red), G (green), and B (blue) as visible data. It is also almost impossible to grasp the chlorophyll distribution in the ocean from the R, G, and B data of color images using aircraft.

There is an urgent need to develop a method of clearly visualizing the distribution of chlorophyll, suspended suspended solids, and red tide in the ocean from terrestrial satellite data or aerial image data including only visible light R, G, and B bands with very poor radiation resolution. . The technical problem to be achieved in the present invention is as follows.

In satellite imagery, the ocean is darker than land, and regional differences in marine characteristics cannot be easily distinguished. These images are mathematically transformed to produce images that can visualize the distribution of phytoplankton and red tide organisms in the ocean.

Normal and near-infrared (NIR) data are used to calculate the Normal Vegetation Index (NDVI), which indicates the degree of plant activity on land. In the present invention, by using only visible light R, G, B band data in the ocean where near-infrared data is not available, an OVE (Ocean Vegetation Index) having properties similar to that of land NDVI is derived and visualized.

Hereinafter, described in detail by the accompanying drawings as follows. 1 is a flowchart of an implementation procedure of the present invention, and FIG. 2 is a main formula used in the present invention.

Referring to Figures 1 and 2 to calculate the marine vegetation index, the specific details of how to clearly visualize the characteristics of the ocean are as follows.

First, R (red), G (green), and B (blue) data are extracted for each pixel of the image data (20). For each pixel, the vegetation indexes I _R , I _G , and I _B of the R, G, and B components are calculated by equation (2) of FIG. 2 (30). The vegetation index calculated by this method is a value in the range (-1, +1), and the vegetation index is calculated in the range of (-1, +1) even in the dark pixels of the image. In order to utilize the C (cyan), M (magenta), and Y (yellow) component color in addition to the R, G, and B component color indices, the calculation is performed using Equation (4) of FIG. 2. In each pixel, color indices of six components of R, G, B, C, and MY can be calculated. In the present invention, the color indices of R, G, and B are mainly utilized.

The green color index I _G calculated by Equation (2) of FIG. 2 is defined as an ocean vegetation index (OVI). From terrestrial satellite data, Red and NIR band data are used to utilize the Normal Vegetation Index (NDVI), which indicates the degree of plant chlorophyll activity. The marine OVI of the present invention is similar in concept to terrestrial NDVI. An image of the marine vegetation index which is converted into an image by scale-converting (40) the value 32 of the OVI calculated as a value in the range (-1, + 1) is made (70). Using a histogram of the distribution of oceanic OVI values for scale transformation of OVI data results in a clearer distribution of chlorophyll (plankton) in the ocean in ocean vegetation index images.

R, G, and B component color indices (32, 34, 36) I _R , I _G , and I _B are scale-converted (50) to red, green, and blue brightness, respectively, and then these three band brightnesses Data are used to create oceanographic visualizations (80). By using the histogram of each band for scale conversion in the marine characteristic image production step, a clearer image can be made. Even if the ocean is dark in the original natural color RGB image, the regional differences in seawater characteristics of each region are clearly displayed in the ocean characteristic visualization image.

The red component color index 36 is scale-converted (60) to produce an image of a red tide distribution, which is a red plant eutrophication phenomenon (90). To make the red tide look more efficient in the red-tide distribution image, scale it so that the area with and without the red tide appears to be a very different image.

The red component and yellow component color indices can be used to determine the distribution of suspended sediments in the ocean, including red and yellow, respectively. The image production method for the suspended suspension distribution uses the same method as the red tide distribution image production (90).

The above-described invention clearly visualizes the distribution of chlorophyll (chlorophyll), red tide, suspended suspension, etc. of the ocean in a satellite image or an aerial image. By deriving and using the relationship between the marine vegetation index and the amount of chlorophyll from the existing marine hygiene data, it is possible to quantitatively calculate the distribution of marine suspended organisms (plankton) from the marine vegetation index of the present invention.

Claims (1)

Computing the color index of the red, green, and blue of the color image in visualizing the characteristics of the ocean in the color image by satellite remote sensing or aerial photography (30) imaging the ocean vegetation index from the green color index (40, 70), visualizing the marine characteristics by combining the red, green, and blue color indices (50, 80), Method for imaging red tide distribution from the red color index (60, 90) and production and distribution of marine vegetation index image, marine characteristic visualization image, ocean red tide distribution image produced using the method .

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