Pros of mozjpeg

• Faster encoding speed than Guetzli
• Supports both lossy and lossless JPEG compression
• More actively maintained with regular updates

Cons of mozjpeg

• Generally produces larger file sizes compared to Guetzli
• Less effective at preserving perceptual quality at very low bitrates

Code Comparison

Guetzli (C++):

std::string CompressJpegXl(const std::vector<uint8_t>& rgb,
                           int xsize, int ysize,
                           float butteraugli_target,
                           ThreadPool* pool) {
  // Compression logic here
}

mozjpeg (C):

GLOBAL(int)
jpeg_write_scanlines(j_compress_ptr cinfo, JSAMPARRAY scanlines,
                     JDIMENSION num_lines) {
  // Compression logic here
}

Both projects aim to improve JPEG compression, but they take different approaches. Guetzli focuses on perceptual optimization and achieving smaller file sizes at the cost of slower encoding, while mozjpeg offers a balance between compression efficiency and encoding speed. Guetzli is written in C++ and uses more modern techniques, whereas mozjpeg is written in C and builds upon the existing libjpeg library. The choice between the two depends on specific use cases and priorities regarding file size, encoding speed, and image quality.

Pros of ImageOptim

• Supports multiple image formats (PNG, JPEG, GIF, etc.)
• Offers a user-friendly GUI for easy image optimization
• Continuously updated with new features and improvements

Cons of ImageOptim

• May not achieve the same level of compression as Guetzli for JPEG images
• Lacks fine-grained control over compression parameters
• Primarily designed for macOS, limiting cross-platform usage

Code Comparison

While both projects focus on image optimization, their implementation and usage differ significantly. Guetzli is primarily used as a command-line tool or library, while ImageOptim offers a GUI application. Here's a basic usage example for each:

Guetzli:

#include "guetzli/processor.h"
std::string in_data = ReadFileOrDie(argv[1]);
std::string out_data;
guetzli::Params params;
ProcessJpegData(params, in_data, &out_data);

ImageOptim:

import ImageOptim

let optimizer = ImageOptimizer()
optimizer.optimize(image: inputImage) { result in
    switch result {
    case .success(let optimizedImage):
        // Use optimized image
    case .failure(let error):
        // Handle error
    }
}

Note that ImageOptim's code is typically used within a macOS application context, while Guetzli's code is more focused on low-level image processing.

Pros of jpeg-archive

• Faster processing times for image compression
• Includes additional tools for image comparison and optimization
• Supports batch processing of multiple images

Cons of jpeg-archive

• Generally produces larger file sizes compared to Guetzli
• May result in lower image quality in some cases
• Less actively maintained (last update was in 2021)

Code Comparison

jpeg-archive:

int compress_jpeg(const char *input, const char *output, int quality, int strip, int progressive) {
    struct jpeg_compress_struct cinfo;
    struct jpeg_error_mgr jerr;
    FILE *infile, *outfile;
    JSAMPARRAY buffer;
    int row_stride;

Guetzli:

bool ProcessJpegData(const JPEGData& jpg_in, const int quality,
                     JPEGData* jpg_out, bool save_jpeg_header) {
  std::vector<uint8_t> rgb_output;
  if (!DecodeJpegToRGB(jpg_in, &rgb_output)) {
    return false;
  }

Both projects focus on JPEG compression, but their approaches and implementations differ. jpeg-archive provides a broader set of tools for image optimization, while Guetzli focuses on high-quality compression at the cost of slower processing times.

Pros of FLAC

• Lossless audio compression, preserving original audio quality
• Widely supported across many devices and platforms
• Open-source and royalty-free format

Cons of FLAC

• Larger file sizes compared to lossy formats
• Not as efficient for image compression (primarily audio-focused)

Code Comparison

FLAC (audio encoding):

FLAC__StreamEncoder *encoder = FLAC__stream_encoder_new();
FLAC__stream_encoder_set_verify(encoder, true);
FLAC__stream_encoder_set_compression_level(encoder, 5);
FLAC__stream_encoder_init_file(encoder, output_filename, NULL, NULL);
FLAC__stream_encoder_process_interleaved(encoder, buffer, samples);

Guetzli (image encoding):

guetzli::ProcessStats stats;
std::string output;
guetzli::Params params;
params.quality = 95;
guetzli::Process(params, &stats, input_rgb, width, height, &output);

FLAC is primarily designed for lossless audio compression, while Guetzli focuses on lossy JPEG image compression. FLAC offers perfect audio reproduction and wide compatibility, but results in larger file sizes. Guetzli aims to produce smaller JPEG files while maintaining visual quality, but is limited to image processing. The code snippets demonstrate their different focuses, with FLAC handling audio streams and Guetzli processing image data.

Pros of libwebp

• Supports both lossy and lossless compression
• Offers animation capabilities (WebP format)
• Faster encoding and decoding compared to Guetzli

Cons of libwebp

• Generally produces larger file sizes than Guetzli for similar quality
• Less effective at preserving fine details in high-quality images

Code Comparison

libwebp

WebPConfig config;
WebPConfigInit(&config);
config.quality = 75;
WebPEncode(&config, &picture);

Guetzli

std::string compressed;
guetzli::Process(params, &processor, input_image, &compressed);

Key Differences

• Guetzli focuses solely on JPEG compression, while libwebp implements the WebP format
• Guetzli aims for higher quality at smaller file sizes, but with slower encoding
• libwebp offers more versatility with animation support and both lossy/lossless options

Use Cases

• Guetzli: High-quality image compression for web content, especially when file size is critical
• libwebp: General-purpose image compression, particularly suitable for websites needing animation support or faster encoding/decoding