

With the introduction of novel image formats, such as QOI, the Quite OK Image format, along with the continuous improvement of existing formats and implementations, measuring the performance of each format for data sets displaying a significant variance in image types is a useful guide to determine the correct codec to pair with each application. Selecting the appropriate format for the target data type might become crucial to the performance of the entire application. From state-of-the-art 4K and 8K video, to ultra-low-power applications, the ratio between the raw image data size and the encoded image size is considered one of the primary metrics to determine the effectiveness of each format, as it is the deciding factor for the storage, and bandwidth in the case of real-time processing, requirements of the application.Ĭompression ratio (CR) may vary between image formats, as well as the type of image data.

LOSSLESS PNG COMPRESSOR REDDIT PROFESSIONAL
The continuous trend of increasing the image resolution in the majority of commercial and professional applications necessitates an ever-evolving set of solutions that facilitate the efficient encoding of images, reducing their size without compromising on quality. The results are then categorized based on the image type to further illustrate the potential effectiveness of each image format for specific use cases. In this paper we attempt to compare the achievable compression ratio of four lossless image formats across a data set of 2814 images exhibiting high variance in their key characteristics.
LOSSLESS PNG COMPRESSOR REDDIT SOFTWARE
From the compression ratio a codec is able to achieve for a specific image type, to algorithmic complexity, speed or memory requirements for a software application, to size and power requirements for a hardware implementation, all constitute deciding factors that will shape the form of the final product. Determining the best fitting lossless image format for a specific application is a process involving the examination of multiple variables in order to make an informed decision.
