Image optimizer

Image compression was born in the 1980s with the first scanners and digital cameras. The JPEG format (1992) revolutionized digital storage with DCT (Discrete Cosine Transform) compression, reducing files by up to 90% without visible loss. Before JPEG, digital photographs occupied megabytes and were impractical to share.

Evolution continued with PNG (1996) for graphics with transparency, animated GIF (1987-1989), WebP (2010) with better compression, and recently AVIF (2020) with artificial intelligence codecs. Today images represent 50% of web weight, making optimization critical for performance.

Image optimization is fundamental for modern SEO. Google prioritizes fast pages in search results, and heavy images are the main cause of slow loading. Each additional second of loading reduces conversions by 7% and increases bounce rate.

Google's Core Web Vitals (LCP, FID, CLS) penalize unoptimized images. A 2MB image can take 8-10 seconds to load on 3G, while an optimized 200KB version loads in less than 1 second. This factor directly impacts organic ranking.

To maximize web performance and user experience, follow these professional recommendations:

1. Choose the right format for each image type

Use JPEG for photographs and images with complex colors (better lossy compression). PNG for logos, icons, and graphics with transparency (lossless compression). WebP for everything (better compression than JPEG and supports transparency), but with fallback. GIF only for simple animations.

2. Adjust quality according to final use

For hero/featured images: 85-90% quality. Content images: 75-80% quality. Thumbnails and miniatures: 60-70% quality. The human eye does not perceive visible differences below 80% in most photographs, achieving savings of 40-60%.

3. Resize before compressing

Never display a 4000x3000px image when the container is 800x600px. Resize to the exact needed size before optimizing. A 4000px image optimized at 80% will still be heavier than an 800px one at 90%.

4. Implement lazy loading and responsive images

Use the loading="lazy" attribute to load images only when visible. Combine with srcset to serve different sizes according to the device. This reduces initial page load by up to 70% on pages with many images.

Image optimization is critical in multiple scenarios: e-commerce (products with multiple photos), blogs and digital magazines (article photographs), creative portfolios (high-resolution galleries), mobile applications (icons and assets), and social networks (avatars and user-generated content).

Companies like Amazon aggressively optimize product images, achieving sub-second loading times. Instagram automatically compresses all uploads to maintain fluid experience. WordPress incorporates automatic optimization since version 5.8 to improve default performance.

The origin of image compression

Image compression was born in the 1980s with the emergence of the first scanners and digital cameras. The JPEG format (Joint Photographic Experts Group), created in 1992, revolutionized digital storage by allowing photographic files to be reduced by up to 90% without visible quality loss. This made it possible to share images over the internet and store them on limited hard drives.

The evolution of formats and algorithms

From classic JPEG, we have evolved towards more modern formats like WebP (2010) from Google, which offers better compression than JPEG and PNG. The AVIF format (2020) uses artificial intelligence to compress images with exceptional quality. Today, automatic optimization is essential for the modern web, where images represent 50% of the total weight of web pages.

Fascinating curiosities about digital images

• The first JPEG: The first compressed JPEG image was a photo of a jazz band called "Lena", which became the standard test image for compression algorithms for decades.
• Lossless vs lossy compression: "Lossless" compression (like PNG) maintains all original information, while "lossy" compression (like JPEG) removes imperceptible data to the human eye, achieving compression rates of up to 95%.
• The human brain: Our brain processes images at about 10-13 Hz, but we can perceive motion at 50-90 Hz. This explains why we can compress images without noticing quality loss.
• Images on the web: An unoptimized image can make a web page take 3-5 seconds longer to load, losing up to 50% of potential visitors.
• Deep Learning: New formats like AVIF use neural networks to predict and compress visual patterns, achieving compression rates impossible with traditional methods.
• The theoretical limit: According to Shannon's information theory, there is no limit to lossless compression, but lossy compression depends on human tolerance for quality loss.