Performance Benchmarks

Understanding performance characteristics is crucial for choosing the right compression strategy. This page provides comprehensive benchmarks across different algorithms, formats, and device capabilities.

Image Compression Performance

Format Comparison - Compression Speed

Processing time for 5MP images (average across 100 samples):

Compression Efficiency Analysis

File size reduction compared to original (average across different image types):

Quality Metrics

Visual quality assessment using SSIM (Structural Similarity Index):

• SSIM > 0.95 - Excellent quality, virtually indistinguishable from original
• SSIM 0.90-0.95 - Very good quality, minor differences under close inspection
• SSIM 0.85-0.90 - Good quality, acceptable for most uses
• SSIM < 0.85 - Noticeable quality degradation

PDF Compression Performance

Processing Speed by Document Type

Average processing time for different PDF types (10MB baseline):

Compression Effectiveness

File size reduction by compression mode:

Device Performance Analysis

Hardware Impact

Performance scaling across different device categories:

Memory Usage Patterns

// Memory consumption during compression
const memoryUsage = {
  // Peak memory usage per 5MP image
  jpeg: '45MB',
  png: '62MB', 
  webp: '58MB',
  avif: '78MB',
  
  // PDF processing (per 10MB document)
  textPDF: '25MB',
  imagePDF: '120MB',
  mixedPDF: '75MB'
}

// Memory-aware batch processing
function calculateOptimalBatchSize(deviceMemory, fileSize) {
  const safetyFactor = 0.7 // Use 70% of available memory
  const availableMemory = deviceMemory * safetyFactor
  const estimatedUsage = fileSize * 3 // Conservative multiplier
  
  return Math.max(1, Math.floor(availableMemory / estimatedUsage))
}

Browser Performance Comparison

Format Support and Speed

Relative performance across major browsers (Chrome baseline = 1.0x):

Web Worker Performance

Performance improvement when using Web Workers:

• Main Thread Blocking - 0% (eliminated with Web Workers)
• Processing Speed - 5-15% faster due to dedicated thread
• Memory Isolation - Better garbage collection and memory management
• User Experience - UI remains responsive during processing

Network Performance Impact

Transfer Time Savings

Time saved during file transfer (1MB original file):

Total Performance Equation

// Calculate total time including compression and transfer
function calculateTotalTime(fileSize, compressionRatio, compressionTime, bandwidth) {
  const compressedSize = fileSize * (1 - compressionRatio)
  const transferTime = compressedSize / bandwidth
  const totalTime = compressionTime + transferTime
  
  return {
    compressionTime,
    transferTime,
    totalTime,
    savings: (fileSize / bandwidth) - totalTime
  }
}

// Example: 5MB image, WebP 80% compression, 2s compression time, 10Mbps connection
const result = calculateTotalTime(5 * 1024 * 1024, 0.8, 2, 1.25 * 1024 * 1024)
// Result: 2.8s total vs 4s without compression = 1.2s saved

Real-World Performance Tips

Optimization Strategies

• Progressive Processing - Start with smallest files for immediate feedback
• Adaptive Quality - Reduce quality for very large files or slow devices
• Format Fallbacks - Use simpler formats on slower devices
• Batch Size Limiting - Process in smaller chunks on mobile devices

Performance Monitoring

// Monitor and adapt to device performance
class PerformanceAdapter {
  constructor() {
    this.metrics = {
      averageProcessingTime: 0,
      memoryPressure: false,
      deviceCapability: this.assessDevice()
    }
  }
  
  assessDevice() {
    const cores = navigator.hardwareConcurrency || 2
    const memory = navigator.deviceMemory || 4
    const connection = navigator.connection?.effectiveType || '4g'
    
    if (cores >= 8 && memory >= 8) return 'high'
    if (cores >= 4 && memory >= 4) return 'medium'
    return 'low'
  }
  
  adaptSettings(baseSettings) {
    const settings = { ...baseSettings }
    
    if (this.metrics.deviceCapability === 'low') {
      settings.quality = Math.max(0.6, settings.quality - 0.1)
      settings.concurrency = 1
      settings.maxFileSize = 5 * 1024 * 1024 // 5MB limit
    }
    
    if (this.metrics.memoryPressure) {
      settings.batchSize = Math.min(5, settings.batchSize)
    }
    
    return settings
  }
}

Benchmarking Your Implementation

Key Metrics to Track

Benchmark Implementation

async function runBenchmark(files, settings) {
  const results = []
  
  for (const file of files) {
    const startTime = performance.now()
    const startMemory = performance.memory?.usedJSHeapSize || 0
    
    try {
      const compressed = await compressFile(file, settings)
      const endTime = performance.now()
      const endMemory = performance.memory?.usedJSHeapSize || 0
      
      results.push({
        fileName: file.name,
        originalSize: file.size,
        compressedSize: compressed.size,
        compressionRatio: (file.size - compressed.size) / file.size,
        processingTime: endTime - startTime,
        memoryUsed: endMemory - startMemory,
        bytesPerSecond: file.size / ((endTime - startTime) / 1000)
      })
    } catch (error) {
      results.push({
        fileName: file.name,
        error: error.message
      })
    }
  }
  
  return analyzeBenchmarkResults(results)
}

Conclusion

Performance optimization requires balancing multiple factors including processing speed, compression efficiency, and user experience. Use these benchmarks as a baseline, but always test with your specific content and target devices.

Key takeaways:

• AVIF provides best compression but slowest processing
• WebP offers good balance of compression and speed
• Device capabilities significantly impact performance
• Web Workers are essential for good user experience
• Adaptive strategies improve performance across diverse devices