The title was just to get your attention. 
The purpose of this thread is purely for awareness of the video artifacts that manifest themselves and descriptions and/or explanations of what they are/look like.
Problems with Digital Video
Distortions that get added to a video signal during digital encoding are known as artifacts.
Here is the 24 bit reference image:
General Problems
Aliasing
Aliasing occurs when a signal being sampled contains frequencies that are too high to be successfully digitised at a given sampling frequency. When sampled these high frequencies fold back on top of the lower frequencies producing distortion. In most methods of video digitising, this will produced pronounced vertical lines in the picture. This problem can be reduced by applying a low pass filter to the video signal before it is digitised to remove the unwanted high frequency components. This is tricky to do without removing some of the wanted high frequency components, and results in softer edges in the picture due to the slower permitted transitions in the signal level.
Aliasing:
Effect of Low-Pass Filtering before Digitising :
Quantisation Noise
This form of distortion occurs because, when digitised, the continuously variable analogue waveform must be quantised into a fixed finite number of levels. It is the coarseness of these levels that causes quantisation noise. A 24-bit colour picture (composed of an 8-bit value for each of the red, green and blue components of each pixel) suffers from virtually no quantisation noise, since the number of available colours is so high - 16.7 million. Reasonable results can be obtained from an 8-bits per pixel picture, especially if the picture is greyscale rather than colour.
8-bits per Pixel:
4-bits per pixel:
Overload
Like quantisation noise, overload is related to the finite number of levels that the signal can take. If a signal is digitised that is too high in amplitude, then the picture will appear bleached. For example, if the signal level of a greyscale image is too high for the conversion process to cope with, then all levels above the maximum will be converted to white, causing the washed out appearance.
Overloading During Conversion:
Digital Signal Degradation
Video in digital form degrades far less gracefully than its analogue counterpart. While digital information may in theory be duplicated an infinite number of times without any degradation, once that degradation does occur, it is very noticeable. Due to the compression techniques used, a single bit error in the data stream could for example cause a large block of pixels to be displayed in a completely different colour to that intended.
An MPEG video frame with multiple bit errors:
Artifacts Caused by Compression
The Gibbs Effect :
One of the most common artifacts that afflicts both MPEG compression is the Gibbs effect. This is most noticeable around artificial objects such as plain coloured, large text and geometric shapes such as squares. It shows up as a blurring or haze around the object, where the sudden transition is made from the artificial object to the background. It is caused by the discrete cosine transform used to digitise chrominance and luminance information. This phenomena is also apparent around more natural shapes like a human figure. The area of the background around the subject appears to shimmer as the subject moves slightly. This shimmering has been nicknamed mosquitos.
Blockiness
Another artifact that affects MPEG is blockiness. When video footage involving high speed motion is digitised, the individual 8x8 blocks that make up the picture become more pronounced.
Blockiness caused by Compression:
Lossy Compression
A lossy compression method allows a system to produce much higher compression ratios. This removes some of the information contained in the signal, hopefully information that will go unnoticed. For example, an encoder may be designed with the criteria of providing output with say a 98% similarity to the input signal. Under most circumstances this may produce an acceptable picture, but if the video footage is a tennis match, then it may quite justifiably ignore the tennis ball (according to the encoding criteria) since it is so small! This kind of behaviour is obviously unacceptable, but lossy compression is very difficult to get right.
The purpose of this thread is purely for awareness of the video artifacts that manifest themselves and descriptions and/or explanations of what they are/look like.
Problems with Digital Video
Distortions that get added to a video signal during digital encoding are known as artifacts.
Here is the 24 bit reference image:
General Problems
Aliasing
Aliasing occurs when a signal being sampled contains frequencies that are too high to be successfully digitised at a given sampling frequency. When sampled these high frequencies fold back on top of the lower frequencies producing distortion. In most methods of video digitising, this will produced pronounced vertical lines in the picture. This problem can be reduced by applying a low pass filter to the video signal before it is digitised to remove the unwanted high frequency components. This is tricky to do without removing some of the wanted high frequency components, and results in softer edges in the picture due to the slower permitted transitions in the signal level.
Aliasing:
Effect of Low-Pass Filtering before Digitising :
Quantisation Noise
This form of distortion occurs because, when digitised, the continuously variable analogue waveform must be quantised into a fixed finite number of levels. It is the coarseness of these levels that causes quantisation noise. A 24-bit colour picture (composed of an 8-bit value for each of the red, green and blue components of each pixel) suffers from virtually no quantisation noise, since the number of available colours is so high - 16.7 million. Reasonable results can be obtained from an 8-bits per pixel picture, especially if the picture is greyscale rather than colour.
8-bits per Pixel:
4-bits per pixel:
Overload
Like quantisation noise, overload is related to the finite number of levels that the signal can take. If a signal is digitised that is too high in amplitude, then the picture will appear bleached. For example, if the signal level of a greyscale image is too high for the conversion process to cope with, then all levels above the maximum will be converted to white, causing the washed out appearance.
Overloading During Conversion:
Digital Signal Degradation
Video in digital form degrades far less gracefully than its analogue counterpart. While digital information may in theory be duplicated an infinite number of times without any degradation, once that degradation does occur, it is very noticeable. Due to the compression techniques used, a single bit error in the data stream could for example cause a large block of pixels to be displayed in a completely different colour to that intended.
An MPEG video frame with multiple bit errors:
Artifacts Caused by Compression
The Gibbs Effect :
One of the most common artifacts that afflicts both MPEG compression is the Gibbs effect. This is most noticeable around artificial objects such as plain coloured, large text and geometric shapes such as squares. It shows up as a blurring or haze around the object, where the sudden transition is made from the artificial object to the background. It is caused by the discrete cosine transform used to digitise chrominance and luminance information. This phenomena is also apparent around more natural shapes like a human figure. The area of the background around the subject appears to shimmer as the subject moves slightly. This shimmering has been nicknamed mosquitos.
Blockiness
Another artifact that affects MPEG is blockiness. When video footage involving high speed motion is digitised, the individual 8x8 blocks that make up the picture become more pronounced.
Blockiness caused by Compression:
Lossy Compression
A lossy compression method allows a system to produce much higher compression ratios. This removes some of the information contained in the signal, hopefully information that will go unnoticed. For example, an encoder may be designed with the criteria of providing output with say a 98% similarity to the input signal. Under most circumstances this may produce an acceptable picture, but if the video footage is a tennis match, then it may quite justifiably ignore the tennis ball (according to the encoding criteria) since it is so small! This kind of behaviour is obviously unacceptable, but lossy compression is very difficult to get right.
