**5. Conclusions and Future Work**

We proposed the original multi-criteria decision-making methodology for the qualitative selection of the lossy compression for the aerial images based on their resolution and content. The transform-based lossy compression algorithms with the appropriate compression ratios were ranked by their suitability for aerial images using MCDM WASPAS-SVNS and direct criteria weights evaluation methods. The rating of lossy compression is governed by the set of qualitative parameters of images and visually acceptable lossy compression ratios.

Because of the need for the qualitative lossy compression for the effective storage and transmission of a large amount of remote sensing data, it is imperative to decide which algorithm and what compression ratio will be suitable for the selected image content and resolution. Since the image quality after lossy compression can be determined by various parameters, and they belong to the different groups that vary significantly, the weighted combination of different qualitative parameters should be used.

The visual features (e.g., a forest, cropland, roads, buildings, water) in an image can be characterized by generalizations like texture, color tone, and luminance. The information on the change of the colors and textures can be calculated using the first-order color statistics and second-order texture statistics, respectively. It is reasonable to include the often-used objective IQA metrics and subjective evaluation. Using the set of the verified groups of parameters and altering their weights, the effect of lossy compression on the image content can be evaluated more precisely compared to the estimation using only single objective image quality metrics.

The use of the set of the qualitative parameters for the texture, color, and IQA, can solve different subtasks: the same approach can be used to assess the texture, color, and general quality after the image lossy compression.

In the aerial imagery application context, it is useful to define the acceptable lossy compression ratio for the selected lossy compression algorithm. We concentrated on visual image inspection after data collection and compression for easier transmission and saving storage space. It should be useful to find the best solution for image lossy compression

implementation in hardware in such cases. The threshold of acceptable visual distortions places the algorithms with their compression ratios in order of priority, excluding those whose distortions are greater than the subjectively determined quality threshold. The experimental results showed that the visually acceptable lossy compression for the highresolution aerial images is: JPEG2000—lower than 100:1 for "img1" and lower than 75:1 for "img2" and "img3"; ECW and JPEG—lower than 75:1 for "img1" (near to 50:1 and less), lower than 50:1 for "img2" and "img3" (near to 25:1 and less). The visually acceptable lossy compression for the low-resolution aerial images is worse than for the high-resolution images: JPEG2000—lower than 75:1 for "img4" and "img5" (near to 50:1 and less), and lower than 50:1 for "img6"; ECW and JPEG—lower than 50:1 for "img4", "img5," and "img6" (near to 25:1 and less).

As the lossy compression quality is a complex task and needs to be investigated further, we are going to evaluate the lossy compression quality for the different classes of satellite images against the segmentation using the appropriate set of qualitative parameters.

**Author Contributions:** Conceptualization, R.B. and G.K.-J.; methodology, R.B., G.K.-J.; software, G.K.-J.; validation, R.B., G.K.-J.; formal analysis, R.B., G.K.-J.; investigation, G.K.-J.; resources, R.B., G.K.-J.; data curation, G.K.-J.; writing—original draft preparation, G.K.-J.; writing—review and editing, R.B., G.K.-J.; supervision, R.B; project administration, R.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** The research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data sharing not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
