How Video Compression Technology Works

Converting a video file such that it takes up less space than the original file and is simpler to send across a network or the Internet is known as video compression. This compression technology reduces the size of video files by deleting redundant material from the original video file.

Anyone reducing video footage typically has the file size as their top priority because huge files slow down simple uploads, transfers, internet streaming, etc. This is because they require more bandwidth and storage space, both of which might be expensive or limited on a video hosting site.

Video compression optimizes the need for storage space, as well as the speed of file transfer and transmission. This makes publishing and sharing videos easier, at the same time giving viewers a seamless streaming experience.

Lossy video compression can cause the image quality to be lower than the original image. The process aims to provide adequate compression methods that produce perceptually lossless quality. In other words, even if the quality of compressed video differs from the original unadulterated video, the variation is very slight for the human eye to detect.

Video information can be represented as a collection of still frames or, as fields in the case of interlaced videos. Video compression algorithms use the spatial and temporal redundancy present in the frame sequence. Most video compression techniques combine spatial compression, which relies on redundant information inside a single frame or field, and temporal compression, which relies on redundant information across consecutive video frames.

Spatial Compression

Techniques for spatial compression are based on the compression of still images. The transform approach is widely used in numerous formats and protocols. This method divides the picture into chunks and applies the transform to each block individually. The transform's output is quantized and scaled. A lossless entropy encoder compresses the quantized data, and the resulting compression is used to create the output bit stream. The Discrete Cosine Transform (DCT) or its variations is the most often used transform algorithm. Other spatial compression methods include fractal compression, wavelet transform, and vector coding.

Temporal Video Compression

Temporal video compression is a highly potent technique. It operates by comparing several video frames to one another. If there are still portions of the video, the system can quickly tell the system to copy those portions bit-for-bit into the next frame. A prediction approach can be used if parts of the pixels are altered relative to the frame or frames (e.g., relocated, rotated, changed brightness, etc.). The algorithm looks for a similar region in the previous frame or frames for each area in the current structure. If a comparable region is discovered, it is removed from the present area, and the transform coder encodes the difference.

A weighted total of the equivalent regions from previous and subsequent frames may also determine the reference for the current frame area. Several frame intervals must delay the current structure if successive frames are utilized.

Compression Standards

Various industry and proprietary video encoding standards exist. Nearly all generally accepted standards are built using DCT transform methods.