Cameras are everywhere these days, observing and recording people, places and things. Most of the time there’s only the one opportunity to capture a moment or an event, and if, for example, the lighting is poor or the camera is out of focus, the quality of the recorded video may render is worthless. This is especially true of video that is to be used as evidence in Court. Video enhancement is a service that can improve the quality of a poorly recorded video.
Forensic vs Non-Forensic Enhancement
Although the work of enhancing an out-of-focus home video is no different to that of enhancing an out-of-focus CCTV recording that will be used as evidence in Court, the way we handle, store and work with each type of video is vastly different.
This covers the enhancement of video that isn’t going to be used as evidence in legal proceedings, for example, enhancing home videos. Although the techniques used to enhance the video and the resulting enhanced video will be the same whether or not we treat it forensically, what will differ greatly is how we approach and document our workflow and how we handle and store the recordings.
In order for evidence to considered reliable its itegrity and authenticity cannot be in doubt. A proper chain of custody is required to demonstrate that the utmost care has been taken to preserve the integrity of the evidence.
When enhancing video for Court purposes it is necessary to establish a proper, auditable, chain of custody. We do so by logging the date/time/place the video was received, who received it, who it was received from, how it was received, a physical description of the item, and references to the customer/case for which the video will be enhanced.
Everything that happens to that video, every time it is moved or used, a full description of who, what, when, where, how and why must be added to the chain of custody document. When not being used, the video is kept under lock and key.
Video Enhancement Techniques
|Technique||What it entails|
|Color Correction or Grading||Recover the colors of the original scene by compensating for varying filming conditions (e.g. poor lighting). Calibrate video camera using a known standard and adjust color mode, brightness, contrast, luminance, saturation and hue.|
|Contrast Adjustment or Histogram Equalization||Intensify contrasts. Change the color palette by equalizing the tonal distribution of the image.|
|De-Interlacing or Motion Compensation||Isolate and analyze separately each interlaced field (with only half the horizontal lines). Combine fields or interpolate missing lines to display full frames.|
|De-Multiplexing||Isolate and analyze separately individual camera views (scenes) that have been recorded sequentially. Reorder the frames by connecting the ones that appear to be similar in content.|
|Edge Enhancement or Sharpening||Enhance the apparent sharpness or definition of the video by creating crisp, high-contrast edges. Identify sharp edge boundaries in the frame (e.g. contours between subject and background) and increase the image contrast in the area immediately around the edges.|
|Frame Averaging||Reduce noise and video graininess. Average each individual pixel from multiple sequential frames.|
|Homomorphic Filtering||Highlight details obscured by shadows (e.g. licence plate in the dark).Simultaneously normalize the brightness and increase contrast.|
|Image Segmentation||Locate or isolate elements and boundaries within the frame (e.g. face recognition, plate recognition). Identify edge boundaries and label every pixel within the frame such that pixels with the same label share certain visual characteristics.|
|Image Stabilization or Tracking||Counteract the visible frame-to-frame jitter caused by subtle camera movements or the motion blur caused by high-speed movement. Distract horizontal and vertical movement or track the target object by slightly shifting the image within each frame.|
|Image Subtraction or Differencing||Isolate patterns or isolate changes between two frames. Capture lightfield (reference) image and subtract from the input image.|
|Inverse Filtering||Recover the original frame from a frame that has been enhanced, degraded or corrupted. Reverse the transformation process applied to the degraded frame.|
|Masking or Blurring||Obscure an area to hide sensitive information (e.g. face, licence plate). Apply a mosaic or blur on the relevant area within the frame.|
|Noise Reduction||See image or frame averaging. See image or frame averaging.|
|Photogrammetric or Geometric Correction||Remove shading artifacts and distortions caused by the mapping of non-planar (e.g. 3D) geometric shapes into a two-dimensional frame. Derive the required spatial transformation by analyzing known reference points.|
|Photogrammetric or Reverse Projection||Derive reliable geometric measurements from a frame (e.g. height, distance, speed). Obtain reference measurements and use a calibrated measurement standard to extrapolate real-world measures.|