Then is it fair for my professor to want me to do PCM on an image in MATLAB to reduce the bits per pixel? I think not but I want confirmation because this is driving me insane.Svein said:No, PCM is a very simple way of coding analog data into a digital data stream. See https://en.wikipedia.org/wiki/Pulse-code_modulation.
The PCM I know is Pulse Code Modulation, which I understand to be the catch-all term for all digitisation. Before we go further, is this what your lecture notes are telling you? On the face of it, he seems to be making an unreasonable demand - but perhaps it's not actually what he said / wrote.Boltzman Oscillation said:Then is it fair for my professor to want me to do PCM on an image in MATLAB to reduce the bits per pixel? I think not but I want confirmation because this is driving me insane.
PCM (Pulse Code Modulation) is a method of converting analog signals into digital signals by sampling the signal at regular intervals and assigning numerical values to each sample. Quantization is the process of converting these numerical values into discrete levels to reduce the amount of data needed to represent the signal.
PCM works by sampling an analog signal at regular intervals and converting each sample into a binary number. These numbers are then transmitted or stored as digital data, which can be reconstructed back into an analog signal by a digital-to-analog converter.
The purpose of quantization in PCM is to reduce the amount of data needed to represent an analog signal. By converting the numerical values into discrete levels, the amount of data can be significantly reduced without losing too much information about the original signal.
There are several advantages of using PCM over analog signals. PCM allows for more efficient transmission and storage of data, as well as better error correction and noise reduction. It also allows for easier processing and manipulation of the signal, making it more versatile for various applications.
The main limitation of quantization in PCM is that it can introduce quantization error, which is the difference between the original analog signal and the reconstructed signal. This can result in a loss of fidelity and accuracy in the reconstructed signal. Additionally, quantization can also introduce distortion in the signal, particularly at lower bit depths.