Linked from

The 34 pages that link to Quantization (signal processing), each with the reason it gives.

• Digital audioRelated: It determines the amplitude precision of sampled audio and contributes quantization noise.

• Analog-to-digital converterRelated: An ADC rounds each sampled amplitude to one of its available digital levels.

• Data compressionRelated: It reduces precision, making it a principal source of information loss in lossy compression.

• Digital imageRelated: It limits each sampled pixel value to representable digital levels.

• Digital signal processingRelated: It accounts for finite numerical precision when analog measurements become digital samples.

• JPEGRelated: JPEG discards precision by coarsening transform coefficients, especially at higher frequencies.

• Dynamic rangeRelated: Finite quantization steps can constrain the smallest distinguishable signal differences.

• Signal processingRelated: It introduces amplitude error when analog signals are encoded digitally.

• Lossy compressionRelated: Coarsening transformed values is a direct way codecs discard information.

• Digital signalRelated: Quantization gives each sampled value one of the signal's permitted levels.

• Analog signalRelated: Quantization removes the continuous amplitude range during digitization.

• Digital-to-analog converterRelated: Finite DAC codes restrict the analog output to discrete nominal levels.

• Audio codecRelated: Lossy audio codecs quantize encoded values, controlling bitrate and introducing distortion.

• Color depthRelated: Finite bit depth forces continuous colors or intensities into discrete levels.

• Image compressionRelated: Lossy image codecs use it to remove precision and reduce the amount of data.

• Video compressionRelated: Coarser coefficient levels lower bitrate while introducing lossy distortion.

• Pulse-code modulationRelated: PCM rounds each sample to one of a finite number of representable levels.

• Digital communicationRelated: It introduces representation error when continuous measurements become digital symbols.

• Video codecRelated: Codec quantization controls much of the balance between bitrate and visible distortion.

• Sound recording and reproductionRelated: Quantization sets the amplitude resolution and contributes digital noise.

• Digital signal processorRelated: Quantization introduces finite-precision error into the samples a DSP stores and computes.

• Fixed-point arithmeticRelated: Fixed-point formats approximate values between their representable levels through quantization.

• Gamma correctionRelated: Nonlinear encoding allocates more code values to darker tones, where visual sensitivity is greater.

• Digital imagingRelated: It sets the available precision for brightness and color values.

• SamplingRelated: It follows sampling in many digital systems but changes amplitude precision, not sample timing.

• Digital dataRelated: It limits sampled measurements to representable digital values.

• Heat mapRelated: Binning values into color bands makes the heat map discrete rather than continuous.

• RGB color spacesRelated: Finite RGB channel bit depth limits how finely colors can be encoded.

• Audio coding formatRelated: Lossy encoders use quantization to reduce the precision and size of audio data.

• CD playerRelated: Each stored audio sample has a limited numerical precision.

• Video coding formatRelated: Lossy formats use quantization to trade fidelity for bitrate.