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This chapter presents our findings from the benchmarking experiments conducted to evaluate the performance of alternative image processing libraries. The results include quantitative data on image conversion and pixel iteration times, as well as memory consumption for each library or combination tested. The data generated will be used to answer the research question and support the hypotheses formulated in the previous chapters. The benchmarking approach consisted of running two primary tests on each library: an image conversion test that measured the time taken to load, process, and save images, and a pixel iteration test that recorded the time required to process every pixel in an image for a grayscale conversion. These experiments were performed in a controlled environment, with warm-up iterations included to reduce the impact of initial overhead. Memory consumption was tracked alongside processing times using BenchmarkDotNet, thereby offering a complete picture of both speed and resource utilization.\\
Before discussing the results in detail, it is important to review the benchmarking design. In this study, each library was tested under the same conditions: the same input image was used, a fixed number of warm-up iterations were performed to reduce the effects of just-in-time compilation and caching, and finally, 100 main iterations were executed to ensure reliable statistics. For the image conversion test, the time measured was the duration needed to load a JPEG image, convert it to PNG, and save it back to disk. In the pixel iteration test, the focus was on recording the time required to access and change each pixel for producing a grayscale version of the image.