According to one implementation, a system for performing automated salience assessment of pixel anomalies includes a computing platform having a hardware processor and a system memory storing a software code. The hardware processor is configured to execute the software code to analyze an image for a presence of a pixel anomaly in the image, obtain a salience criteria for the image when the analysis of the image detects the presence of the pixel anomaly, and classify the pixel anomaly as one of a salient anomaly or an innocuous anomaly based on the salience criteria for the image.
BACKGROUND
Pixel errors in images occur with regularity but can be difficult and costly to identify and correct. For example, anomalous pixels in video frames can be introduced by many different processes within a video production pipeline.
1. A system comprising: a computing platform including a hardware processor and a system memory storing a software code; the hardware processor configured to execute the software code to: analyze an image for a presence of a pixel anomaly in the image; obtain a salience criteria for the image when analysis of the image detects the presence of the pixel anomaly; classify the pixel anomaly as one of a salient anomaly or an innocuous anomaly based on the salience criteria for the image; disregard the pixel anomaly when the pixel anomaly is classified as the innocuous anomaly; and flag the pixel anomaly when the pixel anomaly is classified as the salient anomaly. ||
9. A method for use by a system including a computing platform having a hardware processor and a system memory storing a software code, the method comprising: analyzing the image for a presence of a pixel anomaly in the image; obtaining a salience criteria for the image; classifying the pixel anomaly as one of a salient anomaly or an innocuous anomaly based on the salience criteria for the image; disregarding the pixel anomaly when classified as innocuous; and flagging the pixel anomaly when classified as salient. ||
17. A method for use by a system including a computing platform having a hardware processor and a system memory storing a software code providing a graphical user interface (GUI), the method comprising: analyzing a plurality of segments of video for a presence of a pixel anomaly; for each segment including the pixel anomaly: displaying at least one video frame using the GUI; receiving a salience criteria as an input via the GUI; classifying the pixel anomaly as salient or innocuous; and disregarding the pixel anomaly when classified as innocuous; for all segments, flagging all pixel anomalies classified as salient anomalies.