*4.1. Compression of Aerial Images*

Three lossy compression algorithms were selected for the initial experiment: JPEG200, ECW, JPEG. As the quality of the compressed image depends not only on the compression algorithm but also on the compression ratio, four compression ratios were selected for each algorithm named as follows: low (25:1), medium (50:1), high (75:1), very high (100:1). The influence of the compression ratios lower than 25:1 is negligible, as shown in [19,31,34]. Higher compression ratios deteriorated image quality significantly and were not estimated in this work. Larger intervals between compression ratios were chosen to make their effect on the content of an image more explicit. Each algorithm introduces unique artifacts to the image content that are more noticeable in the higher compression ratios.

The GLOBAL MAPPER software [46] was used for the ECW compression of the original aerial images. The RGB color *\*.tiff* image file saved as the *\*.ecw* image using Global Mapper changing the compression ratios. The *imwrite()* function from MATLAB was used for JPEG2000 and JPEG compression. The source images were obtained as TIFF images with lossless compression. The JPEG2000 compressed files were generated using the *imwrite (* . . . *, "CompressionRatio", Value)* function, altering *Value* for the target compression ratio. For JPEG compression *imwrite (* . . . *, "Quality", Value)* function was used, altering *Value* as the quality from 100 to 1 of the JPEG compressed file. The smaller the number, the more compression will be reached with the worse quality for the image. All other settings for the *imwrite()* function were set to default values. The experimental compression ratios were tailored and verified using Equation (1).

The content and resolution of the image also affect the result of the lossy compressed image. Relevant compression algorithms have different effects on image textures, colors, and luminance. Three high-resolution (1 pixel = 0.5 m) aerial images of different content were selected using Earth Explorer [76]. The aerial images used in the experiment (Figure 4) are "img1", "img2", and "img3" of the dataset *200710\_myrtle\_beach\_sc\_0x5000m\_utm\_clr*, saved as 3000 × 3000 24-bit TIFF images in RGB (8 bits for each band). The "img1" has more smooth textures with low spatial frequencies of intensity changes, and the large regions of different colors and intensities dominate in it. The "img2" is rich with similar rough textures with high spatial frequencies of intensity changes, and small regions occupy a slight part of the image. The "img3" has various types of textures, and a large number of regions differ in size, color, and intensity [27]. We have tested other images with similar textures and colors to verify objective qualitative parameters. Images were selected by the varying characteristic features (texture, color tone, luminance, number, and size of the objects) but not by the appropriate classes, as the aim is to verify the methodology.

For the other three images of different resolutions, the original images were reduced four times using the *impyramid()* MATLAB function. The reduced "img1", "img2", and "img3" will be referenced as "img4", "img5", and "img6" accordingly, with the resolution of 1 pixel = 2 m and the size of 750 × 750 pixels. The remote sensing images with higher spatial resolution have richer spatial textures as their pixels contain more information compared to low-resolution images. All six images of different structures were compressed using three different algorithms using four compression ratios. Figure 5 presents the cropped images "img1" and "img4" compressed using JPEG2000, ECW, and JPEG algorithms at a 100:1 compression ratio.

**Figure 4.** The original aerial images used in the experiment (Landsat-7 images courtesy of the U.S. Geological Survey): (**a**) "img1" in RGB. The red rectangular indicates a cropped region presented in Figure 5); (**b**) "img2" in RGB; (**c**) "img3" in RGB; dataset *200710\_myrtle\_beach\_sc\_0x5000m\_utm\_clr*. (**d**) "img1", component Y; (**e**) "img2", component Y; (**f**) "img3", component Y.

**Figure 5.** The same cropped region of the aerial images "img1" and "img4" compressed using different lossy compression algorithms at the compression ratio 100:1: (**a**) "img1", the original image; (**b**) "img1", Joint Photographic Experts Group (JPEG)2000 compression; (**c**) "img1", Enhanced Compression Wavelet (ECW) compression; (**d**) "img1", JPEG compression; (**e**) "img4", the reduced "img1"; (**f**) "img4", JPEG2000 compression; (**g**) "img4", ECW compression; (**h**) "img4", JPEG compression.
