Is Uneven Blockiness on Lines a Sign of Video Manipulation?

The blocking artifacts are clearly visible in this image. FIGURE 3. Example of compression artifacts: (A) original Lena image and (B) JPEG compressed image at 0.24 bits per pixel. For simplicity, in the rest of the chapter we treat an N × N digital image as an N2 × 1 vector f by scanning either along rows or columns.

It is the core of several industry ... annoying blocking artifacts when they are applied in low bit rate coding to obtain a reasonable compression ratio. The quantization is the lossy stage because the original values of the DCT coefficients are permanently lost. Because each block is encoded separately, there may emerge visible discontinuities along block boundaries ...

Unlike in uncompressed images, when a JPEG compressed image is cropped, there is a change in the inter-block correlation of DCT coefficients due to the shifting of blocking artifacts.

Both of these artifacts are used by several · image forensic algorithms to trace an image’s compression history, identify the device used to create the image, and identify composite ... Laplace distribution. In light of this, we propose the following de- blocking algorithm which is suitable for anti-forensic purposes.

These boundaries can be transform block boundaries, prediction block boundaries, or both, and may coincide with macroblock boundaries. The term macroblocking is commonly used regardless of the artifact's cause. Other names include blocking, tiling, mosaicing, pixelating, quilting, and checkerboarding.

The second type is the tampering operation which is further divided into dependent and · independent. The dependent base depends on the type of forgery carried out on the image, on the other hand, the · independent base depends on artifact traces left during image processing such as compression.

Compression artifacts, such as blockiness, ringing, and banding, are inevitable by-products of lossy image compression. Nowadays, removing these artifacts is routinely handled by deep-learning post-processing.

There are several studies on algorithms for evaluating classical compression artifacts, such as blockiness [] and ringing [], []. However, such artifacts are not inherent to neural codecs, so these algorithms are unable to detect artifacts resulting from neural compression.

Objective evaluation of temporal artifacts is more challenging, though, and popular video quality assessment models often fail to account for them. ... ● Basis Pattern: Taking its name from basis functions (mathematical transforms) endemic to all compression algorithms, it usually occurs in regions like trees, fields of grass, waves, etc. Typically, if viewers notice a basis pattern, it has a strong negative impact on perceived video quality. ● Blocking: Blocking occurs whenever a compressed image is streamed over a low bandwidth connection.