What is a positive image?

Orthographic image, as a digital surveying and mapping product, has geometric accuracy, mathematical accuracy and image characteristics at the same time, and has a large amount of information, rich content, intuitive and true, and broad application prospects. Orthographic image refers to the image after the central projection photo is corrected to a certain extent, which limits the projection error caused by terrain fluctuation and the image point displacement caused by sensor error. The traditional photogrammetry method produces orthophoto images with high accuracy, but it needs aerial photography, aerial photo processing and scanning digitization, as well as accurate field photo control results, indoor photo control point encryption and photo correction processing on the all-digital photogrammetry system, which has long production cycle and high cost, and is difficult to meet the needs of the rapid development of many industries. Using high-resolution satellite images to make orthophoto images is not as accurate as photogrammetry, but it has good effect, strong practicability, easy data acquisition and short production cycle, which can meet the needs of many industries in society and greatly improve production cost and efficiency. Based on this idea, this paper introduces the method of using remote sensing image processing system ERDAS IMAGINE to process IKONOS satellite data and make orthophoto images.

manufacturing method

1, fusion

IKONOS sensor can provide 1m panchromatic band and 4m multispectral (red, green, blue and infrared) band. The purpose of fusion is to combine the high resolution of panchromatic band with the color of multispectral image to produce high resolution multispectral image.

The red, green, blue and infrared spectral bands are combined to generate a quasi-natural color image with 4m resolution. In order to improve the fusion effect, this method adds infrared band to the multi-spectral image, which makes the fused multi-spectral image closer to the natural color than only combining red, green and blue bands.

ERDAS IMAGINE resolution fusion provides three fusion methods: principal component, multiplication and Brovey transform. Principal component is most suitable for requiring the output image to keep the original sensor radiation characteristics (color balance) of multi-spectral images as much as possible, so this method is selected for fusion to keep the quasi-natural color characteristics of multi-spectral images.

After fusion, the infrared band is removed, leaving only the red, green and blue bands. Select an appropriate band sequence to generate a quasi-natural color image with a resolution of1m.

2. Point correction

The autonomous positioning accuracy of Ikonos without ground control points is 12m (plane accuracy) and 10m (elevation accuracy). In order to ensure that the image meets the mapping requirements, image correction is needed. The vector data of Baotou 1: 10000 topographic map has been used. A method of keyboard input control points by quadratic polynomial correction. Firstly, six points are evenly distributed, and then a certain number of redundant control points are added.

Calculation error, residual check and control point X, Y coordinate error. If the mean error exceeds the limit, re-sampling should be done after selecting the control points, and the method of multiple corrections should be adopted.

The resampling process is a process of generating a corrected image according to the pixel values of an uncorrected image. There are three commonly used methods for ERDAS resampling: nearest neighbor interpolation, bilinear interpolation and cubic convolution interpolation, among which bilinear interpolation is usually used for resampling.

Perform coordinate coding after resampling. Image data has coordinate system and projection information. Superimpose the corrected image with 1: 10000 vector data, check the error of image correction, and complete data correction if it meets the requirements. Otherwise, it needs to be corrected again until the tolerance is met.

Step 3 plug in

Mosaic image module for mosaic "date preparation". Histogram matching is carried out before stitching to reduce the tone difference between adjacent images after stitching. When splicing, choose the appropriate matching method and covering method. The matching method is generally "overlapping area", the covering methods are "cutting line exists" and "cutting/feathering by distance", and the feathering distance is generally 2 or 3, which makes the stitching more natural on the premise of ensuring accuracy.

Step 4 cut

After stitching is completed, DOM with 1: 10000 standard framing is generated according to the coordinates of the required map sheet. The "subset image" module of "DatePrep" image processed by PhotoShop will lose some coordinate information. Before processing, the header file *. The TFW of each DOM is established according to the coordinate values of "image information". Tone processing is carried out under PhotoShop to make the tones of adjacent sheets basically the same. Finally, the map is cropped to generate a digital orthophoto map.

Concluding remarks

The method reduces the production cost and improves the production efficiency. The disadvantage is limited accuracy, but it can meet the different needs of different industries.

If you want to make high-precision DOM from Ikonos data, you can use Ikonos stereo satellite images to generate DOM, or use existing DEM to correct it.