# Product Image Generation Method Based on Morphological Optimization and Image Style Transfer
## 2 Literature Review
### Aesthetic Evaluation of Product Form  
As living standards improve, individuals increasingly pursue not only material enjoyment but also a higher quality of life. Products with esthetic attributes resonate deeply with consumers' inner emotions, fulfilling their emotional desires. The esthetic appeal of product design has the power to influence people's thoughts, moods, and emotional development. Consequently, excellent product design should also embody an esthetically pleasing appearance. The evaluation of product esthetics centers on users' cognitive activities, involving comparisons, assessments, and judgments of product appearance and esthetic evaluation based on their individual esthetic interests, concepts, and preferences [6]. These evaluation results serve as a crucial basis for purchase decision-making. Traditional studies of esthetics have primarily focused on philosophical discussions, viewing esthetics as implicit knowledge that is difficult to articulate and considering it subjective, arbitrary, and ambiguous. However, with the emergence of modern esthetics and advancements in science and technology, computational esthetics has rapidly emerged as a research focal point in the fields of digital industrial design and art design. Computational esthetics objectively and quantitatively constructs the relationship between the formal characteristics of objects and esthetic experience, transforming esthetics from implicit to explicit knowledge, thereby offering a novel methodology and approach for esthetics research.  
In recent years, significant advancements have been made in the research on esthetic evaluation of product forms, particularly in the realms of esthetic knowledge representation, application patterns, experimental methodologies, and modeling techniques. [PERSON] et al. [7] formulated three esthetic index formulas for balance, contrast, and harmony according to esthetic principles. Utilizing linear regression, they established an esthetic evaluation model tailored for interfaces. Meanwhile, [PERSON] [8] constructed formulas for product form esthetic indexes such as symmetry, simplicity, and cohesion. [PERSON] et al. [9] adopted factor analysis to extract six primary esthetic indexes from interfaces, using the variance contribution rates of the indexes as weights to construct a comprehensive esthetic evaluation model. [PERSON] et al. [10] analyzed curve organizational characteristics and, guided by Gestalt principles, established six esthetic index formulas utilizing vector products: proximity, continuity, closure, symmetry, directionality, and similarity. [PERSON] et al. [11] took a water bottle as an example and, based on Gestalt principles, proposed calculation methods for three indexes: symmetry, similarity, and continuity. They also explored the esthetic utility of these indicators through discrete-choice experiments in virtual reality. [PERSON] et al. [12] simplified the graphic elements in the interface to rectangles and constructed formulas for 13 esthetic indexes, applying computational esthetics methods to quantify the esthetic appeal of image elements. [PERSON] et al. [13] formulated 15 esthetic index formulas based on esthetic principles and Gestalt principles and established a comprehensive esthetic evaluation model for product form using principal component analysis. These aforementioned studies have provided valuable insights into the research on esthetic evaluation of products. However, they primarily concentrate on the representation of relatively straightforward indexes, resulting in an esthetic index system that lacks comprehensiveness. For some of these esthetic indexes with complex connotations, due to their characteristics of polysemy, fuzziness, and uncertainty, it is difficult to represent them accurately. Current research in this area is still inadequate. Therefore, it is necessary to conduct in-depth research on esthetic measure indexes with complex connotations.