Deep Learning Empowers Next-Gen Video Compression: Bridging Quality and Efficiency
Mohammad Khadir, Mohammad Farukh Hashmi, Mohammad Khadir · 2023
Deep learning accelerates video processing. Our digital exchanges increasingly use video. Technology has raised video resolutions and volumes, making collection, distribution, compression, and display tougher. This paper introduces flask-based Deep Learning video compression. Good treatment results. This technique expertly blends Deep Learning's adversarial generative and convolutional neural networks. Convolutional and adversarial generating networks are CNN and GAN. GAN detects minute changes, LSTM captures them, and image repetition reduces video. Reduces files. Steps after layer grouping. GAN's incremental updates compress frames better than the original image. This reduces compressed videos. SVD finds latent components in video frames. This reduces R, G, B utility matrix dimension. KNN calculates each frame image's neighbor connection. Comparison results are classified by K-means. Codecs compare frames to their original video formats. Comparison follows video translation. Resampling rates were statistically significant in many experiments with movies of different lengths, resolutions, FPS, and quality. 10% lower quality and 50% smaller than the original video.