Image Compression and Decompression
i. Encoding and Decoding of Image compression and decompression
-Encoding - Image compression algorithms analyze images to reduce redundancy and eliminate irrelevant information while preserving visual quality.
- Decoding - Decoding involves reconstructing the original image from the compressed data using the inverse of the compression algorithm.
ii. Advantages and Disadvantages of Image compression and decompression
-Advantages
- Reduces storage space and bandwidth requirements for images.
- Enables efficient transmission of images over networks.
- Can provide high-quality images at lower bitrates.
- Disadvantages
- Lossy compression algorithms may introduce perceptible artifacts in the image.
- Compression and decompression can be computationally intensive, especially for high-resolution images.
iii. Application areas for Image compression and decompression
- Web graphics - Image compression is crucial for fast loading times and efficient delivery of images on websites.
- Medical imaging - Lossless compression techniques are used to preserve diagnostic image quality in medical applications.
Performance issues for Image compression and decompression
- Timing - Compression and decompression times vary depending on the complexity of the image data and the compression algorithm.
- Compression factor - The compression factor depends on the desired image quality and the compression algorithm used.
- Suitability for Real-Time - Real-time image compression and decompression require efficient algorithms to minimize latency, particularly in applications such as video conferencing or surveillance systems.
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