CCTV Video Compression: Techniques, Codecs and Storage Calculation

A single 1080p CCTV camera recording round the clock can fill more than a terabyte of storage every month. Multiply that by hundreds of cameras and 30 to 90 days of retention, and storage quickly becomes one of the biggest costs of running a surveillance system. Video compression is how organisations keep that cost under control without losing the detail they need for investigations.

Quick answer: CCTV video compression reduces the size of recorded footage by removing repeated information within and between frames. Modern codecs like H.264 and H.265 use interframe compression to cut storage by 50% or more, while smart codecs and AI-based tools reduce it further by recording less data when nothing is happening in the scene.

What is CCTV Video Compression?

CCTV Video Compression refers to the technique or combination of techniques used to decrease the storage size of video files, captured through CCTV surveillance cameras, by removing redundant frames and employing other optimisation algorithms. With increasing demand for CCTV Surveillance Systems in business places as well as in urban infrastructural applications, CCTV Video Compression is becoming the need of the hour, to control storage costs while optimising for video quality. While storage compression technologies have been there in the Indian markets for more than a decade, these conventional compression technologies involved significant loss in video footage quality, thereby making it difficult to utilise the recordings later for identifying nuisance-makers, decipher vehicle registration numbers and such other applications.

The main problems posed by such conventional Video Compression technologies are:

• Video Resolution and Quality Issues, especially with growing demand for 4K and higher resolutions.

• Intensive CPU Utilisation due to complexity of the algorithm, increasing hardware load on NVRs and servers.

• Compatibility across Codecs, emerging standards and Video Formats.

• Inefficiency in inter-frame compression for scenes with complex textures and too many motions.

• Unintended noise and distortions may creep into the footage for conventional algorithms.

Types of CCTV Video Compression

Broadly there are two approaches to CCTV Video Compression:

Interframe Compression

Interframe compression uses the similarity between successive frames. The encoder stores a complete keyframe, called an I-frame, and then records only the changes in the following frames - P-frames (predicted from earlier frames) and B-frames (predicted from both earlier and later frames), using motion estimation to track moving objects. Because a static CCTV scene changes very little from one frame to the next, this approach saves a lot of space. H.264 (AVC), H.265 (HEVC) and MPEG-4 are the most common interframe codecs in CCTV, and H.265 typically needs around half the bitrate of H.264 for similar quality.

Intraframe Compression

Intraframe compression treats every frame as a standalone image and compresses it independently, without referring to any other frame. Every frame can be viewed on its own, which makes editing and frame-by-frame review easier, but files are much larger than with interframe codecs. It uses techniques such as Discrete Cosine Transform (DCT), Vector Quantisation, Fractal Compression and Discrete Wavelet Transform (DWT). MJPEG (Motion JPEG), Wavelet and JPEG 2000 are the common intraframe formats, and today they are mainly used where every single frame must be preserved at full quality.

Smart Codecs and AI-Based Compression

Most modern IP cameras and NVRs add a smart codec layer on top of H.264 or H.265 (often branded H.264+ or H.265+). These lower the bitrate when the scene is static, compress the background more than moving objects, and adjust the keyframe interval automatically. AI-based compression goes a step further by recognising people and vehicles, keeping them sharp while compressing the rest of the frame harder.

How to Calculate CCTV Storage Requirements?

Cloud Storage for Surveillance Cameras is one of the most critical cost centres for any workplace facility, and hence organisations are always assessing ways to reduce their CCTV Cloud Storage costs. However, it is always recommended to get in touch with organisations having strong expertise in surveillance, like Transline Technologies, to calculate your CCTV Cloud Storage requirements, and make accurate projections of your video surveillance cloud storage costs.

Resolution

The resolution expectations vary according to the domain of application and even across organisations in the same domain of business. For instance, for smart traffic management, very high resolution footages need to be stored to identify defaulter vehicles by their registration plates.

Compression

The codec your cameras and recorder use has a big impact on storage. Interframe codecs like H.265 need far less space than H.264, and both need much less than intraframe formats like MJPEG.

Bitrate

Higher camera bitrate implies higher video quality and resultant requirement of greater video surveillance cloud storage capacity. Modern CCTV camera systems often use Variable Bit Rate (VBR), which adjusts the bitrate according to the extent of motion and activity in the scene being recorded.

Number of CCTV Cameras

The storage capacity requirement is directly proportional to the number of CCTV cameras whose video feeds are stored. Some modern CCTV storage compression algorithms optimise for motion detection, thereby saving CCTV cloud storage space when no movement is detected in the surveillance zone.

Storage Duration

The longer the duration for which CCTV video footage is to be stored, the higher the video surveillance cloud storage capacity required. Typical storage durations vary between 30 days, 45 days, 60 days and 90 days, depending on the business case or the organisation’s security compliance standards.

CCTV Storage Calculation Formula

You can estimate storage with this simple formula:

Storage (GB) = Bitrate (Mbps) x 3600 x Recording hours per day x Days x Number of cameras / 8 / 1000

For example, one 1080p camera recording 24 hours a day at 4 Mbps (H.264) needs about 43 GB per day, or roughly 1.3 TB for 30 days. The same camera on H.265 at about 2 Mbps needs roughly 650 GB for 30 days. For 100 cameras, that difference is around 65 TB of storage. For more ways to bring this down, see our tips to optimise CCTV camera storage costs and best practices in CCTV footage storage management.

Key Challenges With CCTV Video Compression

Although CCTV Video Compression techniques are becoming increasingly popular, they have their own limitations. We would like to highlight some of these challenges, so that you can adapt your business expectations accordingly.

Quality Loss

Although modern video compression solutions smartly address quality loss issues, these cannot be absolutely eliminated – some choppiness and delays may creep into the video footage.

Storage gaps are not only caused by compression. Cameras that go offline or are tampered with also leave holes in the footage, which tools like CheckCam help detect. Read how to prevent CCTV camera tampering and recording downtime.

Incompatibility with Facial Recognition & Video Analytics Solutions

Due to some redundant frames being removed by the video compression algorithm or some frames compressed very sharply, the compressed footage may not remain compatible with AI powered Video Analytics or Facial Recognition algorithms. Though these solutions mostly work with live footages, which are processed before compression, some use cases may arise in the law-and-order enforcement space, where older footages may need to be processed with FR solutions for identification of criminals or nuisance-makers.

Processing Costs

While storage costs are controlled by using video compression software, processing costs may increase, because encoding and decoding need more CPU or GPU capacity and more power on recording servers and NVRs.

Software Subscription Costs

Implementation of video compression software involves some costs, although at a net level, it helps cut down on storage costs. Hence, organisations prefer a SaaS model for CCTV video compression software, so that they can spread the costs across the lifetime, rather than incurring a one-time capital expenditure.

Reimagining CCTV Storage Efficiency with CAMSTORE

At Transline Technologies, we understand the pain-points of organisations, centred around high storage costs and ease of access of stored CCTV video footage. Hence, we have developed CAMSTORE, a revolutionary tool, which helps organisations save up to 90% on storage costs without compromising on video quality. We have solved most of the challenges discussed above with our advanced compression algorithms.

Unlike other CCTV Storage Compression Solutions, CAMSTORE ensures high footage quality with visually lossless compression, while having the provisions for Cloud Integration and Scalability. Moreover, CAMSTORE is compatible with existing CCTV hardware infrastructure, and hence new CCTV cameras need not be purchased, thereby saving on capital expenditure. We have implemented CAMSTORE in Government organisations and private enterprises across Retail, Healthcare, Logistics & Warehousing, Manufacturing, E-Commerce, Banking & Finance and other sectors.

CAMSTORE works alongside Transline's video surveillance solutions and CamPulse VMS, so recording, compression and video management run on one platform.

Connect with our Solutions Team today to understand how you can tackle the challenges associated with CCTV video compression and CCTV video storage for your organisation.