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Gilles
Gilles
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I understood that SNR is the ratio of signal power to the noise power. In terms of images, how the original image is affected by the added noise. In PSNR, we take the square of the peak value in the image (in case of an 8 bit image, the peak value is 255) and divide it by the mean square error. The SNR and PSNR are used to measure the quality of an image after the reconstruction. I understand that higher the SNR or PSNR, the reconstruction is good. What I don't understand is how SNR and PSNR differs in terms of their conclusion about the reconstructed image. What the PSNR of an image concludes that the SNR of the same image can't conclude ? Simply how the conclusion of PSNR differs from the conclusion of SNR? Please help me.What I don't understand is how SNR and PSNR differs in terms of their conclusion about the reconstructed image.

  • What the PSNR of an image concludes that the SNR of the same image can't conclude ?
  • Simply how the conclusion of PSNR differs from the conclusion of SNR?

I understood that SNR is the ratio of signal power to the noise power. In terms of images, how the original image is affected by the added noise. In PSNR, we take the square of the peak value in the image (in case of an 8 bit image, the peak value is 255) and divide it by the mean square error. The SNR and PSNR are used to measure the quality of an image after the reconstruction. I understand that higher the SNR or PSNR, the reconstruction is good. What I don't understand is how SNR and PSNR differs in terms of their conclusion about the reconstructed image. What the PSNR of an image concludes that the SNR of the same image can't conclude ? Simply how the conclusion of PSNR differs from the conclusion of SNR? Please help me.

I understood that SNR is the ratio of signal power to the noise power. In terms of images, how the original image is affected by the added noise. In PSNR, we take the square of the peak value in the image (in case of an 8 bit image, the peak value is 255) and divide it by the mean square error. The SNR and PSNR are used to measure the quality of an image after the reconstruction. I understand that higher the SNR or PSNR, the reconstruction is good. What I don't understand is how SNR and PSNR differs in terms of their conclusion about the reconstructed image.

  • What the PSNR of an image concludes that the SNR of the same image can't conclude ?
  • Simply how the conclusion of PSNR differs from the conclusion of SNR?
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Premnath D
Premnath D
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Difference between SNR and PSNR

I understood that SNR is the ratio of signal power to the noise power. In terms of images, how the original image is affected by the added noise. In PSNR, we take the square of the peak value in the image (in case of an 8 bit image, the peak value is 255) and divide it by the mean square error. The SNR and PSNR are used to measure the quality of an image after the reconstruction. I understand that higher the SNR or PSNR, the reconstruction is good. What I don't understand is how SNR and PSNR differs in terms of their conclusion about the reconstructed image. What the PSNR of an image concludes that the SNR of the same image can't conclude ? Simply how the conclusion of PSNR differs from the conclusion of SNR? Please help me.