## 2 Image Manipulating Methods  
Based on existing research [10; 11; 12; 13; 14; 15; 16] in the field of image manipulation, several types of modifications to the original image at the pixel level can be identified. One such technique is steganography [15; 16], which involves covert communication by embedding a hidden message within an overt medium. In this context, it refers to embedding data in the spatial domain of the image (pixel values) or the frequency domain (e.g., using Discrete Cosine Transform, DCT). This manipulation is typically minimal, often altering the least significant bits of the image. High-entropy regions are often chosen for such modifications, as they enable changes that remain imperceptible to human perception [17]. Steganography stands out as one of two image processing techniques (alongside digital watermarking) that aim to minimize alterations to the structure of the original image. When we speak of image manipulation, we often refer to actions that alter the interpretation of the photograph. Based on research [18; 19], several primary types of such operations can be identified:  
* Retouching involves subtle modifications aimed at enhancing aesthetics or removing minor imperfections without significantly altering the semantics of the image or its overall message. Retouching may include adjustments to color, contrast, lighting, depth of field, and the elimination of unwanted artifacts such as noise, discoloration, or vignetting. Such techniques are commonly employed in photography to  
Figure 1: An example of reality falsification by a totalitarian regime: the removal of [PERSON] from a photograph with [PERSON] [4]. improve the visual appeal of an image from the viewer's perspective, thereby influencing its emotional impact. Retouching is frequently used in portrait, fashion, and advertising photography. * The copy-and-move operation involves duplicating a single object or a group of objects within the same image. This process is often supplemented by geometric transformations, such as rotation or perspective changes, as well as pixel value modifications, including blurring, contrast adjustment, and brightness regulation. Since the manipulation occurs within a single image, the objects share similar characteristics (having been captured at the same time and scene using the same sensor). This makes the transformation relatively straightforward to execute, making it one of the most commonly encountered types of image manipulation. * The object removal operation affects the semantics of the image and is typically executed using the \"copy-and-move\" technique, where the pixels of the target object are overwritten with pixels sourced from another part of the image. Alternatively, it may involve completely removing and replacing the object's pixels with pixels from surrounding areas, such as the background, to achieve a visually coherent result. * The image compositing operation combines elements from different sources to create a cohesive image. This process results in a new scene that does not exist in reality but is composed of actual objects that were previously captured. This technique is commonly used to manipulate a given shot, altering the context of the individuals or objects depicted within it. * Painting is the process of creating graphic elements to replace portions of the original image. Similar to \"copy-and-move\" or \"object removal\" operations, the goal is to alter the semantics of the image. However, the critical difference is that the new elements are entirely generated from scratch and do not originate from any other pre-existing photograph. The aforementioned manipulations rely on modifications to the original image. Detecting potential fraud can therefore involve comparing the transformed version with the original. As noted in the introduction, recent breakthroughs in deep learning have introduced revolutionary changes across various fields, opening new possibilities for data processing and generation.