Overview

Image Compression by Protein Metrics is a cutting-edge software solution designed to provide higher compression rates than JPEG while maintaining fast throughput and eliminating visible artifacts. This software is specifically tailored for digital pathology applications, where the quality and speed of image compression are critical. The patented Protein Metrics compression algorithm is optimized for automated microscope and whole-slide imagery, ensuring efficient and high-quality image management.

Features

• Higher Compression Rates: Achieve higher compression rates than JPEG without compromising image quality. The Protein Metrics algorithm is designed to avoid block artifacts and "ringing" at sharp edges, which are common issues with JPEG compression.
• Fast Throughput: Benefit from fast compression and decompression speeds, enabling efficient data transfer and compact archiving. The algorithm is multi-threaded and highly parallelized, running at least 10 times faster than standard approaches.
• Lossless to High Compression: Scale from completely lossless to very high compression, depending on your needs. This flexibility allows users to balance between image quality and file size.
• Brightfield and Fluorescence: Applicable to both brightfield and fluorescence microscopy images, making it versatile for various digital pathology applications.
• 1GB per Second: Achieve compression speeds of up to 1GB per second on a typical desktop with an Intel i7 4-core processor, significantly enhancing workflow efficiency.
• Image Management: Streamline image workflows and unlock the full potential of your visual content. Manage images from multiple sources, reduce storage costs, and improve application performance.
• No Visible Artifacts: Ensure high-quality compression with no visible artifacts, preserving the integrity of critical information in microscope imagery.
• Cloud and Local Deployment: The software can be deployed locally or in the cloud, providing flexibility to meet different organizational needs. For users requiring more processing power, the algorithm can be scaled to run in the cloud.